RESPOND-Registry data-All

This report is step one of a three step process for data organization in the RESPOND study. The three steps include:

1. Data processing: investigation and reporting
   • Evaluate the data received from the SEER registries and scantron surveys
     
   • Understand the the variables, their values, distributions, and identify potential problems
     
   • From this report we can propose potential solutions on how to handle missing or unknown data, alternative values, or duplicated or problematic records
     
2. Data cleaning
   • Implement solutions for data cleaning given decisions from step 1 report
     
   • Keep data in detailed format
     
   • Create composite variables
     
3. Data creation
   • Output data to an “analysis ready” R data set
     
   • Output data to a file that facilitates input into SAS

The working dataset used in this report results in a database join of all Scantron Surveys currently processed with all Cancer Registry files received to date from study centers, which were able to be linked based on available identifiers.
- This working dataset was created on 2.8.2020
- The dataset includes 2167 records
- The dataset includes 532 variables
- Variables include: registryid, naaccrrecordversion, tumorrecordnumber, addratdxstate, countyatdx, countyatdxgeocode2000, countyatdxgeocode2010, censustract2000, censustract2010, maritalstatusatdx, race1, race2, race3, race4, race5, spanishhispanicorigin, nhiaderivedhisporigin, ihslink, racenapiia, sex, ageatdiagnosis, dateofbirth, birthplace, birthplacestate, birthplacecountry, censusblockgroup2000, censusblockgroup2010, censustrcertainty2000, censustrcertainty2010, sequencenumbercentral, dateofdiagnosis, primarysite, grade, diagnosticconfirmation, typeofreportingsource, histologictypeicdo3, behaviorcodeicdo3, primarypayeratdx, seersummarystage2000, seersummarystage1977, derivedsummarystage2018, summarystage2018, eodprimarytumor, eodregionalnodes, eodmets, derivedeod2018t, eodextension, derivedeod2018m, eodextensionprostpath, eodlymphnodeinvolv, derivedeod2018n, derivedeod2018stagegroup, regionalnodespositive, regionalnodesexamined, tnmpatht, tnmpathn, tnmpathm, tnmpathstagegroup, tnmclint, tnmclinn, tnmclinm, tnmclinstagegroup, ajcctnmclint, ajcctnmclinn, ajcctnmclinm, ajcctnmclinstagegroup, ajcctnmpatht, ajcctnmpathn, ajcctnmpathm, ajcctnmpathstagegroup, tumormarker2, rxdatesurgery, rxdateradiation, rxdatechemo, rxdatehormone, rxdatebrm, rxdateother, dateinitialrxseer, rxdatedxstgproc, rxsummtreatmentstatus, rxsummsurgprimsite, rxsummscopereglnsur, rxsummsurgothregdis, reasonfornosurgery, rxsummradiation, rxsummsurgradseq, rxsummchemo, rxsummhormone, rxsummbrm, rxsummother, radregionaldosecgy, radregionalrxmodality, rxsummsystemicsurseq, rxsummsurgsite9802, rxsummscopereg9802, rxsummsurgoth9802, dateoflastcontact, vitalstatus, survdateactivefollowup, survdatepresumedalive, survdatedxrecode, causeofdeath, csextension, cslymphnodes, csmetsatdx, cssitespecificfactor7, cssitespecificfactor8, cssitespecificfactor9, cssitespecificfactor10, cssitespecificfactor11, cssitespecificfactor12, cssitespecificfactor13, cssitespecificfactor14, cssitespecificfactor15, cssitespecificfactor1, cssitespecificfactor2, cssitespecificfactor3, cssitespecificfactor4, cssitespecificfactor5, cssitespecificfactor6, derivedajcc6t, derivedajcc6n, derivedajcc6m, derivedajcc6stagegrp, derivedss1977, derivedss2000, comorbidcomplication1, comorbidcomplication2, comorbidcomplication3, comorbidcomplication4, comorbidcomplication5, comorbidcomplication6, comorbidcomplication7, comorbidcomplication8, comorbidcomplication9, comorbidcomplication10, icdrevisioncomorbid, rxdatemostdefinsurg, radboostrxmodality, radboostdosecgy, rxdatesystemic, rxsummtransplntendocr, derivedajcc7t, derivedajcc7n, derivedajcc7m, derivedajcc7stagegrp, derivedseerpathstggrp, derivedseerclinstggrp, derivedseercmbstggrp, derivedseercombinedt, derivedseercombinedn, derivedseercombinedm, secondarydiagnosis1, secondarydiagnosis2, secondarydiagnosis3, secondarydiagnosis4, secondarydiagnosis5, secondarydiagnosis6, secondarydiagnosis7, secondarydiagnosis8, secondarydiagnosis9, secondarydiagnosis10, gleasonpatternsclinical, gleasonpatternspathological, gleasonscoreclinical, gleasonscorepathological, gleasontertiarypattern, gradeclinical, gradepathological, numberofcoresexamined, numberofcorespositive, prostatepathologicalextension, psalabvalue, rid, recno, siteid, surveyid, locationname, respondid, methodology, a1month, a1year, a1not, a2, a3_1, a3_2, a3_3, a3_4, a3_5, a3_6, a3_7, a3_8, a3_9, a3_10, a3_11, a3_12, a3_13, a3_14, a3_15, a3_16, a3_17, a3_18, a3_19, a3_20, a3_21, a3_22, a3_23, a3_24, a3other, a4month, a4year, a5, a5other, a6, a6other, a7, a7other, a8, b1aa, b1ab, b1ac, b1bno, b1ba, b1ba2, b1bb, b1bc, b1cno, b1ca, b1ca2, b1cb, b1cc, b1da, b1db, b1dc, b1ea, b1eb, b1ec, b2, b2a_1, b2a_2, b2a_3, b2a_4, b2a_5, b2a_6, b2a_7, b2b_1, b2b_3, b2b_4, b2b_5, b2b_6, b2b_7, b2cno, b2c_1, b2c_2, b2c_3, b2c_4, b2c_5, b2c_6, b2c_7, b2dno, b2d_1, b2d_3, b2d_4, b2d_5, b2d_6, b2d_7, b2eno, b2e_1, b2e_2, b2e_3, b2e_4, b2e_5, b2e_6, b2e_7, b2fno, b2f_1, b2f_3, b2f_4, b2f_5, b2f_6, b2f_7, b3, b4aa, b4ab, b4ba, b4bb, b4ca, b4cb, b4da, b4db, b4dc, b4ea, b4eb, b4fa, b4fb, b4fc, b4ga, b4gb, b4ha, b4hb, b4ia, b4ib, b4ja, b4jb, b4jc, b4jd, b4ka, b4kb, b4la, b4lb, b4ma, b4mb, b4na, b4nb, b4oa, b4ob, b4pa, b4pb, b4qa, b4qb, b4qother, b5, b5other, c1, c2a1, c2a2, c2a3, c2b1, c2b2, c2b3, c2c1, c2c2, c2c3, c3a1, c3a2, c3a3, c3b1, c3b2, c3b3, c3c1, c3c2, c3c3, c3d1, c3d2, c3d3, c4a1, c4a2, c4a3, c4b1, c4b2, c4b3, c4c1, c4c2, c4c3, c4d1, c4d2, c4d3, c4e1, c4e2, c4e3, d1aa, d1ab, d1ba, d1bb, d1ca, d1cb, d1da, d1db, d1ea, d1eb, d1fa, d1fb, d1ga, d1gb, d2a, d2b, d2c, d2d, d2e, d3a1, d3a2, d3a3, d3b1, d3b2, d3b3, d3c1, d3c2, d3c3, d3d1, d3d2, d3d3, d3e1, d3e2, d3e3, d3f1, d3f2, d3f3, d3g1, d3g2, d3g3, d3h1, d3h2, d3h3, d3i1, d3i2, d3i3, d3j1, d3j2, d3j3, d4a, d4b, d4c, d4d, d4e, d4f, d4g, d4h, d4i, d4j, d4k, d4l, d5a, d5b, d5c, d5d, d5e, d5f, d5g, d5h, d5i, d5j, d5k, e1_1, e1_2, e1_3, e1_4, e1_5, e1_6, e1other, e2aa, e2ab, e2ba, e2bb, e3, e4, e5, e6, e7, e8, e9_1, e9_2, e9_3, e9_4, e9_5, e9_6, e9_7, e9_8, e9_9, e9_10, e10_1, e10_2, e10_3, e10_4, e10_5, e10_6, e10_7, e10_8, e10_3_1, e10_3_2, e10_3_3, e10_4_1, e10_4_2, e10_4_3, e10_5_1, e10_5_2, e10_5_3, e10_5_4, e10_5_5, e11a, e11b, e11c, e11d, e11e, e11f, e12, e13, e14, e15, f1ft, f1in, f1cm, f2lbs, f2kgs, f3, f4, f5, f6, f7, f7age, f7a, f7b, f7bage, g1, g2_1, g2_2, g2_3, g2_4, g2_5, g3, g3other, g4a, g4b, g4c, g5, g5other, g6_1, g6_2, g6_3, g6_4, g6_5, g6_6, g6_7, g6_8, g7, g8, g9a, g9b, g9c, g10, g10other, g11, g12

SITE ID

• Codes
  • 10 Greater CA
  • 20 Georgia
  • 25 North Carolina
  • 30 Northern CA
  • 40 Louisiana
  • 50 New Jersey
  • 60 Detroit
  • 61 Michigan
  • 70 Texas
  • 80 Los Angeles County
  • 81 USC-Other
  • 82 USC-MEC
  • 90 New York
  • 94 Florida
  • 95 WebRecruit-Limbo
  • 99 WebRecruit

  siteid <- as.factor(trimws(d[,"siteid"]))
  #new.d.n <- data.frame(new.d.n, siteid) # keep NAACCR coding
  
  # NEED REGISTRY NAMES!!
 
  
  #replace number with names
  
  levels(siteid)[levels(siteid)=="80"] <- "Los Angeles County.80"
  levels(siteid)[levels(siteid)=="30"] <- "Northern CA.30"
  levels(siteid)[levels(siteid)=="10"] <- "Greater CA.10"
  levels(siteid)[levels(siteid)=="60"] <- "Detroit.60"
  levels(siteid)[levels(siteid)=="40"] <- "Louisiana.40"
  levels(siteid)[levels(siteid)=="20"] <- "Georgia.20"
  levels(siteid)[levels(siteid)=="61"] <- "Michigan.61"
  
  
  new.d <- data.frame(new.d, siteid)
  new.d <- apply_labels(new.d, siteid = "Site ID")
  new.d.1 <- data.frame(new.d.1, siteid)
  
  #cro(new.d$siteid) # this is pretty but doesn't show NAs
  #summary(new.d$siteid)
  
  #Using kable function to form a nice table
  
  siteid_count<-count(new.d$siteid)
  colnames(siteid_count)<- c("Registry", "Total")
  kable(siteid_count, format = "simple", align = 'l', caption = "Overview of 7 Registries")

Overview of 7 Registries

Registry	Total
Greater CA.10	237
Georgia.20	1087
Northern CA.30	174
Louisiana.40	290
Detroit.60	174
Michigan.61	16
Los Angeles County.80	189

NAACCR RECORD VERSION

• Description: This item applies only to record types I, C, A, and M. Code the NAACCR record version used to create the record. The correction record (U) has its own record version data item.
• Rationale: The NAACCR Layout version is necessary to communicate to the recipient of data in NAACCR form where the various items are found and how they are coded. It should be added to the record when the recorded is created.
• Codes
  • 120 2010 Version 12
  • 121 2011 Version 12.1
  • 122 2012 Version 12.2
  • 130 2013 Version 13
  • 140 2014 Version 14
  • 150 2015 Version 15
  • 160 2016 Version 16
  • 180 2018 Version 18
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#50

  naaccrrecordversion <- as.factor(trimws(d[,"naaccrrecordversion"]))
  
  
  levels(naaccrrecordversion)[levels(naaccrrecordversion)=="180"] <- "2018_Version_18.180"

  
  new.d <- data.frame(new.d, naaccrrecordversion)
  new.d <- apply_labels(new.d, naaccrrecordversion = "naaccr Record Version")
  new.d.1 <- data.frame(new.d.1, naaccrrecordversion)
  
  #cro(new.d$siteid) # this is pretty but doesn't show NAs
  #summary(new.d$siteid)
  
  #Using kable function to form a nice table
  
  naaccrrecordversion<-count(new.d$naaccrrecordversion)
  colnames(naaccrrecordversion)<- c("Version", "Total")
  kable(naaccrrecordversion, format = "simple", align = 'l', caption = "Overview of Version")

Overview of Version

Version	Total
2018_Version_18.180	2167

TUMOR RECORD NUMBER

• Description: A system-generated number assigned to each tumor. The number should never change even if the tumor sequence is changed or a record (tumor) is deleted.
• Rationale: This is a unique number that identifies a specific tumor so data can be linked. “Sequence Number” cannot be used as a link because the number is changed if a report identifies an earlier tumor or if a tumor record is deleted.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#60

All data

st_css() #IMPORTANT!

  tumorrecordnumber <- as.factor(trimws(d[,"tumorrecordnumber"]))
  
  new.d <- data.frame(new.d, tumorrecordnumber)
  new.d <- apply_labels(new.d, tumorrecordnumber = "tumor record number")
  new.d.1 <- data.frame(new.d.1, tumorrecordnumber)
  
  #Using kable function to form a nice table

  temp.d <- data.frame (new.d.1, tumorrecordnumber)
  summarytools::view(dfSummary(new.d$tumorrecordnumber, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumorrecordnumber [labelled, factor]	tumor record number	1. 0 2. 1 3. 2 4. 3 5. 4	402 ( 18.6% ) 1648 ( 76.0% ) 102 ( 4.7% ) 12 ( 0.6% ) 3 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	178 ( 94.2% ) 4 ( 2.1% ) 5 ( 2.6% ) 2 ( 1.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	0 ( 0.0% ) 165 ( 94.8% ) 6 ( 3.4% ) 2 ( 1.1% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	224 ( 94.5% ) 2 ( 0.8% ) 11 ( 4.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	0 ( 0.0% ) 155 ( 89.1% ) 15 ( 8.6% ) 3 ( 1.7% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	0 ( 0.0% ) 278 ( 95.9% ) 10 ( 3.4% ) 2 ( 0.7% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	0 ( 0.0% ) 1029 ( 94.7% ) 54 ( 5.0% ) 3 ( 0.3% ) 1 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumor_record_number [factor]	1. 0 2. 1 3. 2 4. 3 5. 4	0 ( 0.0% ) 15 ( 93.8% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

ADDR AT DX–STATE

• Description: Identifies the patient’s state or province of residence at the time of diagnosis as identified by the Reporting Source. For consolidated records, the state may be based on reported or corrected residential address information.

• Rationale: The state of residence is part of the patient’s demographic data and has multiple uses. It can be used to evaluate referral patterns, allows for the analysis of cancer cluster concerns, and supports epidemiological studies that use area-based social measures.

• Instructions for Coding

  • This field is intended to store residential state for the patient’s physical, residential address. The state for PO Box mailing address should not be entered into this data item except in the infrequent case when no other address information is available.
  • If the patient has multiple tumors, state at diagnosis may be different for each tumor.
  • Do not update this item if the patient’s residential address changes. Store address update information in the affiliated current address data items. Only update based on improved information on the residential address at time of diagnosis. For instance, it is appropriate to correct a state during the geocoding or consolidation process.
  • Use the U.S. Postal Service abbreviation (for the state, territory, commonwealth, U.S. possession) or Canada Post abbreviation (for the Canadian province/territory) in which the patient resides at the time the reportable tumor is diagnosed.
  • If the patient is a foreign resident, then code either XX or YY depending on the circumstance.

• Codes (in addition to USPS abbreviations)

  • CD Resident of Canada, NOS (province/territory unknown)
  • US Resident of United States, NOS (state/commonwealth/territory/possession unknown)
  • XX Resident of country other than the United States (including its territories, commonwealths, or possessions) or Canada, and country is known
  • YY Resident of country other than the United States (including its territories, commonwealths, or possessions) or Canada, and country is unknown
  • ZZ Residence unknow

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#80

All data

st_css() #IMPORTANT!

  addratdxstate <- as.factor(trimws(d[,"addratdxstate"]))
  
  new.d <- data.frame(new.d, addratdxstate)
  new.d <- apply_labels(new.d, addratdxstate = "addr at dx--state")
  new.d.1 <- data.frame(new.d.1, addratdxstate)
  
  #Using kable function to form a nice table

  temp.d <- data.frame (new.d.1, addratdxstate)
  summarytools::view(dfSummary(new.d$addratdxstate, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addratdxstate [labelled, factor]	addr at dx--state	1. CA 2. GA 3. LA 4. MI	600 ( 27.7% ) 1087 ( 50.2% ) 290 ( 13.4% ) 190 ( 8.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	189 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	237 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	0 ( 0.0% ) 0 ( 0.0% ) 290 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	0 ( 0.0% ) 1087 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	addr_at_dx_state [factor]	1. CA 2. GA 3. LA 4. MI	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COUNTY AT DX REPORTED

• Description: Identifies the

• Description: Code for the county of the patients residence at the time of diagnosis as identified by the Reporting Source. For U.S. residents, standard codes are those of the FIPS publication Counties and Equivalent Entities of the United States, Its Possessions, and Associated Areas or their equivalent INCITS codes.

• Calculating county and county-based variable rates using this item is not recommended. The more specific, geocoded county items should be used when available.

• Rationale: This data item may be used for epidemiological purposes. For example, to measure cancer incidence in a particular geographic area.

• Instructions for Coding

  • This field is intended to store address information for the patient’s physical, residential address. All efforts should be made to find the patient’s true street address and postal code, including reviewing relevant sources outside the medical record if available. The county for a PO Box mailing address should only be recorded when no other address information is available in the medical record and no other information sources are available.
  • If the patient has multiple tumors, county at diagnosis may be different for each tumor.
  • Do not update this item if the patient’s county of residence changes. Store updated address information in the affiliated current address data items. Only update based on improved information on the residential address at time of diagnosis. For instance, it is appropriate to correct county during a consolidation process.
  • This variable is coded at time of abstracting and is considered less accurate than the derived, geocoded county at diagnosis variables: County at Diagnosis 1990, 2000, 2010, & 2020.
  • Detailed standards have not been set for Canadian provinces/territories. Use code 998 for Canadian residents.

• Codes (in addition to FIPS and Geocodes)

  • 001-997 Valid FIPS code
  • 998 Known town, city, state, or country of residence but county code not known AND a resident outside of the state of reporting institution (must meet all criteria). Use this code for Canadian residents.
  • 999 The county of the patient is unknown, or the patient is not a United States resident. County is not documented in the patient’s medical record.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#90

All data

st_css() #IMPORTANT!

  countyatdx <- as.factor(trimws(d[,"countyatdx"]))
  
  new.d <- data.frame(new.d, countyatdx)
  new.d <- apply_labels(new.d, countyatdx = "addr at dx--state")
  new.d.1 <- data.frame(new.d.1, countyatdx)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, countyatdx)
  summarytools::view(dfSummary(new.d$countyatdx, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	countyatdx [labelled, factor]	addr at dx--state	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	75 ( 3.5% ) 4 ( 0.2% ) 18 ( 0.8% ) 10 ( 0.5% ) 5 ( 0.2% ) 7 ( 0.3% ) 2 ( 0.1% ) 11 ( 0.5% ) 25 ( 1.2% ) 5 ( 0.2% ) 2 ( 0.1% ) 5 ( 0.2% ) 143 ( 6.6% ) 1 ( 0.0% ) 40 ( 1.8% ) 11 ( 0.5% ) 2 ( 0.1% ) 47 ( 2.2% ) 5 ( 0.2% ) 2 ( 0.1% ) 63 ( 2.9% ) 1 ( 0.0% ) 8 ( 0.4% ) 5 ( 0.2% ) 3 ( 0.1% ) 1 ( 0.0% ) 9 ( 0.4% ) 32 ( 1.5% ) 9 ( 0.4% ) 3 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 136 ( 6.3% ) 1 ( 0.0% ) 4 ( 0.2% ) 18 ( 0.8% ) 5 ( 0.2% ) 4 ( 0.2% ) 3 ( 0.1% ) 7 ( 0.3% ) 1 ( 0.0% ) 14 ( 0.6% ) 4 ( 0.2% ) 16 ( 0.7% ) 2 ( 0.1% ) 2 ( 0.1% ) 4 ( 0.2% ) 6 ( 0.3% ) 1 ( 0.0% ) 2 ( 0.1% ) 26 ( 1.2% ) 1 ( 0.0% ) 35 ( 1.6% ) 17 ( 0.8% ) 1 ( 0.0% ) 12 ( 0.6% ) 5 ( 0.2% ) 2 ( 0.1% ) 3 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 45 ( 2.1% ) 20 ( 0.9% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 9 ( 0.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 10 ( 0.5% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 5 ( 0.2% ) 2 ( 0.1% ) 7 ( 0.3% ) 6 ( 0.3% ) 8 ( 0.4% ) 1 ( 0.0% ) 13 ( 0.6% ) 2 ( 0.1% ) 6 ( 0.3% ) 2 ( 0.1% ) 1 ( 0.0% ) 5 ( 0.2% ) 4 ( 0.2% ) 7 ( 0.3% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 43 ( 2.0% ) 2 ( 0.1% ) 193 ( 8.9% ) 6 ( 0.3% ) 3 ( 0.1% ) 2 ( 0.1% ) 10 ( 0.5% ) 841 ( 38.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 189 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	73 ( 42.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 39 ( 22.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 60 ( 34.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 4.6% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 205 ( 86.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 34 ( 19.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 125 ( 71.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 15 ( 8.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	1 ( 0.3% ) 4 ( 1.4% ) 13 ( 4.5% ) 9 ( 3.1% ) 0 ( 0.0% ) 6 ( 2.1% ) 2 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 5 ( 1.7% ) 4 ( 1.4% ) 1 ( 0.3% ) 1 ( 0.3% ) 3 ( 1.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 15 ( 5.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 39 ( 13.4% ) 1 ( 0.3% ) 4 ( 1.4% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 148 ( 51.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	1 ( 0.1% ) 0 ( 0.0% ) 4 ( 0.4% ) 1 ( 0.1% ) 4 ( 0.4% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 23 ( 2.1% ) 4 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 139 ( 12.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 0.7% ) 2 ( 0.2% ) 6 ( 0.6% ) 5 ( 0.5% ) 2 ( 0.2% ) 63 ( 5.8% ) 1 ( 0.1% ) 8 ( 0.7% ) 5 ( 0.5% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 32 ( 2.9% ) 9 ( 0.8% ) 3 ( 0.3% ) 2 ( 0.2% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 4 ( 0.4% ) 3 ( 0.3% ) 5 ( 0.5% ) 4 ( 0.4% ) 3 ( 0.3% ) 7 ( 0.6% ) 1 ( 0.1% ) 14 ( 1.3% ) 4 ( 0.4% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 4 ( 0.4% ) 6 ( 0.6% ) 1 ( 0.1% ) 2 ( 0.2% ) 26 ( 2.4% ) 1 ( 0.1% ) 35 ( 3.2% ) 17 ( 1.6% ) 1 ( 0.1% ) 12 ( 1.1% ) 5 ( 0.5% ) 2 ( 0.2% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.2% ) 45 ( 4.1% ) 20 ( 1.8% ) 2 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.2% ) 2 ( 0.2% ) 9 ( 0.8% ) 1 ( 0.1% ) 1 ( 0.1% ) 10 ( 0.9% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 7 ( 0.6% ) 6 ( 0.6% ) 8 ( 0.7% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 6 ( 0.6% ) 2 ( 0.2% ) 1 ( 0.1% ) 5 ( 0.5% ) 4 ( 0.4% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 1 ( 0.1% ) 0 ( 0.0% ) 6 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.1% ) 8 ( 0.7% ) 410 ( 37.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 18.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COUNTY AT DX GEOCODE2000

• Description: Code for the county of the patient’s residence at the time the tumor was diagnosed is a derived (geocoded) variable based on Census Boundary files from 2000 Decennial Census. This code should be used for county and county-based (such as CHSDA) rates and analysis for all cases diagnosed in 2000-2009.

• Rationale: Census tracts are areas geographically nested within counties and designated with a 6-digit number code. This 6-digit code is commonly repeated within a state in different counties. Census tract numbers are only unique when paired with the state and the county. Therefore, a tract cannot be accurately identified without knowing the county. Example from Massachusetts: Rural Franklin County contains a tract 040600 with 2010 population 4,612 people. Urban Suffolk County contains a tract 040600 with 2,444 people. The county must be known in order to distinguish between the two tract codes. Because we historically used a single variable for county at diagnosis [90], correct tract codes were frequently paired with the wrong county due to incorrect county assignment during abstracting or a change of county over time. Also, some variables, such as the Census Tr Poverty Indicatr [145] require the use of the decennial Census County codes closest to year of diagnosis and not the decade of year of diagnosis. Using a single county at diagnosis, and using the reported versus geocoded data, may result in erroneous assignment of geographic location as well as invalid links with census data (i.e., population, poverty category, urban/rural designation).

• Instructions for Coding

  • This variable is generated through the process of geocoding either during abstracting or at the central registry level.
  • It is recommended that all cases diagnosed through 2009 have a geocoded County at Diagnosis 2000.
  • At a minimum, all cases diagnosed through 1996-2009 should have a geocoded County at Diagnosis 2000. Cases diagnosed 1996-1999 must have both County at Diagnosis 1990 and County at Diagnosis 2000 codes for proper assignment of the Census Tract Poverty Indicator [145]. Cases diagnosed 2006-2009 must have both County at Diagnosis 2000 and County at Diagnosis 2010 codes for proper assignment of the Census Tract Poverty Indicator [145].
  • If the patient has multiple tumors, geocoded county may be different for each tumor.
  • Do not update this item if the patient’s county of residence changes. Store updated address information in the affiliated current address data items. Only update based on improved information on the residential address at time of diagnosis. For instance, it is appropriate to correct a county during manual geocoding or a consolidation process.
  • PO Box address information should not be used to geocode this data item except in the infrequent case when no other address information is available.
  • Detailed standards have not been set for Canadian provinces/territories. Use code 998 for Canadian residents.
  • Blank “Not geocoded” is allowable for cases diagnosed before 1995 and after 2009. However, it is recommended to have all cases geocoded to a 2000 Census County to allow for both retrospective and cross-sectional analyses.

• Codes

  • 001-997 County at diagnosis. Valid FIPS code.
  • 998 Known town, city, state, or country of residence but county code not known AND a resident outside of the state of reporting institution (must meet all criteria). Use this code for Canadian residents.
  • 999 County unknown. The county of the patient is unknown, or the patient is not a United States resident. County is not documented in the patient’s medical record.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#95

All data

st_css() #IMPORTANT!

  countyatdxgeocode2000 <- as.factor(trimws(d[,"countyatdxgeocode2000"]))
  
  new.d <- data.frame(new.d, countyatdxgeocode2000)
  new.d <- apply_labels(new.d, countyatdxgeocode2000 = "county at dx geocode 2000")
  new.d.1 <- data.frame(new.d.1, countyatdxgeocode2000)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, countyatdxgeocode2000)
  summarytools::view(dfSummary(new.d$countyatdxgeocode2000, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	countyatdxgeocode2000 [labelled, factor]	county at dx geocode 2000	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	1 ( 0.4% ) 1 ( 0.4% ) 11 ( 4.5% ) 1 ( 0.4% ) 2 ( 0.8% ) 5 ( 2.0% ) 7 ( 2.9% ) 1 ( 0.4% ) 10 ( 4.1% ) 17 ( 6.9% ) 2 ( 0.8% ) 31 ( 12.7% ) 31 ( 12.7% ) 51 ( 20.8% ) 35 ( 14.3% ) 11 ( 4.5% ) 2 ( 0.8% ) 16 ( 6.5% ) 4 ( 1.6% ) 6 ( 2.4% )		1922 (88.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	1 ( 0.4% ) 1 ( 0.4% ) 11 ( 4.6% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 3.0% ) 1 ( 0.4% ) 10 ( 4.2% ) 17 ( 7.2% ) 2 ( 0.8% ) 31 ( 13.1% ) 31 ( 13.1% ) 51 ( 21.5% ) 35 ( 14.8% ) 11 ( 4.6% ) 2 ( 0.8% ) 16 ( 6.8% ) 4 ( 1.7% ) 5 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		173 (99.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_dx_geocode_2000 [factor]	1. 103 2. 107 3. 111 4. 113 5. 125 6. 163 7. 19 8. 25 9. 29 10. 59 11. 61 12. 65 13. 67 14. 71 15. 73 16. 77 17. 83 18. 95 19. 97 20. 99	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 28.6% ) 4 ( 57.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% )		9 (56.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COUNTY AT DX GEOCODE2010

• Description: County at Diagnosis 2010 Code for the county of the patient’s residence at the time the tumor was diagnosed is a derived (geocoded) variable based on Census Boundary files from 2010 Decennial Census. This code should be used for county and county-based (such as CHSDA) rates and analysis for all cases diagnosed in 2010-2019.

• Rationale: Census tracts are areas geographically nested within counties and designated with a 6-digit number code. This 6-digit code is commonly repeated within a state in different counties. Census tract numbers are only unique when paired with the state and the county. Therefore, a tract cannot be accurately identified without knowing the county. Example from Massachusetts: Rural Franklin County contains a tract 040600 with 2010 population 4,612 people. Urban Suffolk County contains a tract 040600 with 2,444 people. The county must be known in order to distinguish between the two tract codes. Because we historically used a single variable for county at diagnosis [90], correct tract codes were frequently paired with the wrong county due to incorrect county assignment during abstracting or a change of county over time. Also, some variables, such as the Census Tr Poverty Indicatr [145] require the use of the decennial Census County codes closest to year of diagnosis and not the decade of year of diagnosis. Using a single county at diagnosis, and using the reported versus geocoded data, may result in erroneous assignment of geographic location as well as invalid links with census data (i.e., population, poverty category, urban/rural designation).

• Instructions for Coding

  • This variable is generated through the process of geocoding either during abstracting or at the central registry level.
  • It is recommended that all cases diagnosed through 2019 should have a geocoded County at Diagnosis 2010.
  • At a minimum, all cases diagnosed through 2006-2019 should have a geocoded County at Diagnosis 2010. Cases diagnosed 2006-2009 must have both County at Diagnosis 2000 and County at Diagnosis 2010 codes for proper assignment of the Census Tract Poverty Indicator [145]. Cases diagnosed 2016-2019 must have both County at Diagnosis 2010 and County at Diagnosis 2020 codes for proper assignment of the Census Tract Poverty Indicator [145].
  • If the patient has multiple tumors, geocoded county may be different for each tumor.
  • Do not update this item if the patient’s county of residence changes. Store updated address information in the affiliated current address data items. Only update based on improved information on the residential address at time of diagnosis. For instance, it is appropriate to correct a county during manual geocoding or a consolidation process.
  • PO Box address information should not be used to geocode this data item except in the infrequent case when no other address information is available.
  • Detailed standards have not been set for Canadian provinces/territories. Use code 998 for Canadian residents.
  • Blank “Not geocoded” is allowable for cases diagnosed before 2005 and after 2019. However, it is preferred to have all cases geocoded to a 2010 Census County to allow for both retrospective and cross-sectional analyses.

• Codes

  • 001-997 County at diagnosis. Valid FIPS code.
  • 998 Known town, city, state, or country of residence but county code not known AND a resident outside of the state of reporting institution (must meet all criteria). Use this code for Canadian residents.
  • 999 County unknown. The county of the patient is unknown, or the patient is not a United States resident. County is not documented in the patient’s medical record.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#96

All data

st_css() #IMPORTANT!

  countyatdxgeocode2010 <- as.factor(trimws(d[,"countyatdxgeocode2010"]))
  
  new.d <- data.frame(new.d, countyatdxgeocode2010)
  new.d <- apply_labels(new.d, countyatdxgeocode2010 = "county_at_dx_geocode_2010")
  new.d.1 <- data.frame(new.d.1, countyatdxgeocode2010)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, countyatdxgeocode2010)
  summarytools::view(dfSummary(new.d$countyatdxgeocode2010, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	countyatdxgeocode2010 [labelled, factor]	county_at_dx_geocode_2010	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	75 ( 3.5% ) 4 ( 0.2% ) 18 ( 0.8% ) 10 ( 0.5% ) 5 ( 0.2% ) 7 ( 0.3% ) 2 ( 0.1% ) 11 ( 0.5% ) 25 ( 1.2% ) 5 ( 0.2% ) 2 ( 0.1% ) 5 ( 0.2% ) 143 ( 6.6% ) 1 ( 0.0% ) 40 ( 1.8% ) 11 ( 0.5% ) 2 ( 0.1% ) 47 ( 2.2% ) 5 ( 0.2% ) 2 ( 0.1% ) 63 ( 2.9% ) 1 ( 0.0% ) 8 ( 0.4% ) 5 ( 0.2% ) 3 ( 0.1% ) 1 ( 0.0% ) 9 ( 0.4% ) 32 ( 1.5% ) 9 ( 0.4% ) 3 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 136 ( 6.3% ) 1 ( 0.0% ) 4 ( 0.2% ) 18 ( 0.8% ) 5 ( 0.2% ) 4 ( 0.2% ) 3 ( 0.1% ) 7 ( 0.3% ) 1 ( 0.0% ) 14 ( 0.6% ) 4 ( 0.2% ) 16 ( 0.7% ) 2 ( 0.1% ) 2 ( 0.1% ) 4 ( 0.2% ) 6 ( 0.3% ) 1 ( 0.0% ) 2 ( 0.1% ) 26 ( 1.2% ) 1 ( 0.0% ) 35 ( 1.6% ) 17 ( 0.8% ) 1 ( 0.0% ) 12 ( 0.6% ) 5 ( 0.2% ) 2 ( 0.1% ) 3 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 45 ( 2.1% ) 20 ( 0.9% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 9 ( 0.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 10 ( 0.5% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 5 ( 0.2% ) 2 ( 0.1% ) 7 ( 0.3% ) 6 ( 0.3% ) 8 ( 0.4% ) 1 ( 0.0% ) 13 ( 0.6% ) 2 ( 0.1% ) 6 ( 0.3% ) 2 ( 0.1% ) 1 ( 0.0% ) 5 ( 0.2% ) 4 ( 0.2% ) 7 ( 0.3% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 43 ( 2.0% ) 2 ( 0.1% ) 192 ( 8.9% ) 6 ( 0.3% ) 3 ( 0.1% ) 2 ( 0.1% ) 10 ( 0.5% ) 841 ( 38.8% )		1 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 188 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1 (0.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	73 ( 42.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 39 ( 22.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 60 ( 34.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 4.6% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 205 ( 86.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 34 ( 19.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 125 ( 71.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 15 ( 8.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	1 ( 0.3% ) 4 ( 1.4% ) 13 ( 4.5% ) 9 ( 3.1% ) 0 ( 0.0% ) 6 ( 2.1% ) 2 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 5 ( 1.7% ) 4 ( 1.4% ) 1 ( 0.3% ) 1 ( 0.3% ) 3 ( 1.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 15 ( 5.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 39 ( 13.4% ) 1 ( 0.3% ) 4 ( 1.4% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 148 ( 51.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	1 ( 0.1% ) 0 ( 0.0% ) 4 ( 0.4% ) 1 ( 0.1% ) 4 ( 0.4% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 23 ( 2.1% ) 4 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 139 ( 12.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 0.7% ) 2 ( 0.2% ) 6 ( 0.6% ) 5 ( 0.5% ) 2 ( 0.2% ) 63 ( 5.8% ) 1 ( 0.1% ) 8 ( 0.7% ) 5 ( 0.5% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 32 ( 2.9% ) 9 ( 0.8% ) 3 ( 0.3% ) 2 ( 0.2% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 4 ( 0.4% ) 3 ( 0.3% ) 5 ( 0.5% ) 4 ( 0.4% ) 3 ( 0.3% ) 7 ( 0.6% ) 1 ( 0.1% ) 14 ( 1.3% ) 4 ( 0.4% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 4 ( 0.4% ) 6 ( 0.6% ) 1 ( 0.1% ) 2 ( 0.2% ) 26 ( 2.4% ) 1 ( 0.1% ) 35 ( 3.2% ) 17 ( 1.6% ) 1 ( 0.1% ) 12 ( 1.1% ) 5 ( 0.5% ) 2 ( 0.2% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.2% ) 45 ( 4.1% ) 20 ( 1.8% ) 2 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.2% ) 2 ( 0.2% ) 9 ( 0.8% ) 1 ( 0.1% ) 1 ( 0.1% ) 10 ( 0.9% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 7 ( 0.6% ) 6 ( 0.6% ) 8 ( 0.7% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 6 ( 0.6% ) 2 ( 0.2% ) 1 ( 0.1% ) 5 ( 0.5% ) 4 ( 0.4% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 1 ( 0.1% ) 0 ( 0.0% ) 6 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.1% ) 8 ( 0.7% ) 410 ( 37.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	county_at_d_geocode_2010 [factor]	1. 1 2. 101 3. 103 4. 105 5. 107 6. 109 7. 11 8. 111 9. 113 10. 115 11. 117 12. 119 13. 121 14. 123 15. 125 16. 127 17. 129 18. 13 19. 131 20. 133 21. 135 22. 137 23. 139 24. 141 25. 145 26. 149 27. 15 28. 151 29. 153 30. 155 31. 157 32. 161 33. 163 34. 167 35. 169 36. 17 37. 171 38. 175 39. 177 40. 179 41. 183 42. 185 43. 189 44. 19 45. 191 46. 193 47. 195 48. 199 49. 201 50. 207 51. 21 52. 213 53. 215 54. 217 55. 219 56. 223 57. 225 58. 23 59. 231 60. 233 61. 235 62. 239 63. 243 64. 245 65. 247 66. 249 67. 25 68. 251 69. 253 70. 255 71. 257 72. 259 73. 261 74. 263 75. 267 76. 269 77. 27 78. 273 79. 275 80. 277 81. 285 82. 289 83. 29 84. 293 85. 297 86. 299 87. 301 88. 303 89. 305 90. 31 91. 311 92. 315 93. 321 94. 33 95. 35 96. 37 97. 39 98. 41 99. 43 100. 45 [ 30 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 18.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CENSUS TRACT 2000

• Description: Identifies the patient’s census tract of residence at the time the tumor was diagnosed. Census Tract 2000 is a derived (geocoded) variables based on the Census Boundary files from 2000. See Census Tract 70/80/90 [110]; Census Tract 2010 [135]; Census Tract 2020 [125]. Codes are those used by the U.S. Census Bureau for the Year 2000 Census. For consolidated records, the geocoded state should be based on the best address at diagnosis information identified.

• Rationale: Census tract codes allow central registries to calculate incidence rates for geographical areas having population estimates. This field allows a central registry to add Year 2020 Census tracts to tumors diagnosed in previous years, without losing the codes in data items [110], [130] and [135].

• The Census Bureau provides population and other demographic data for census tracts. This allows for small area analysis for general surveillance or special geographical and socioeconomic analysis.

• Instructions for Coding

  • This variable is generated through the process of geocoding either during abstracting or at the central registry level.
  • Census tract codes have a 4-digit basic number and also may have a 2-digit suffix. Census tract numbers range from 0001.00 to 9999.98, but the decimal should not be retained in the NAACCR layout.
  • It is recommended that all cases diagnosed through 2009 should have a geocoded Census Tract 2000.
  • At a minimum, all cases diagnosed through 1996-2009 should have a geocoded Census Tract 2000. Cases diagnosed 1996-1999 must have both State at DX Geocode 70/80/90 [82] and State at DX 2000 Geocode [83] codes for proper assignment of the Census Tr Poverty Indicatr [145]. Cases diagnosed 2006-2009 must have both State at DX 2000 Geocode [83] and State at DX Geocode 2010 [84] codes for proper assignment of the Census Tr Poverty Indicatr [145].
  • If the patient has multiple tumors, geocoded state at diagnosis may be different for each tumor.
  • Do not update this item if the patient’s tract of residence changes. Store updated address information in the affiliated current address data items. Only update based on improved information on the residential address at time of diagnosis. For instance, it is appropriate to correct a tract during manual geocoding or a consolidation process.
  • PO Box address information should not be used to geocode this data item except in the infrequent case when no other address information is available.
  • Blank “Not geocoded” is allowable for cases diagnosed before 1995 and after 2009. However, it is recommended to have all cases geocoded to a 2000 Census Tract to allow for both retrospective and cross-sectional analyses.

• Codes

  • 000100-999998 Valid FIPS code
  • 000000 Area not census tracted
  • 999999 Area census-tracted, but census tract is not available
  • Blank Census Tract 2000 not coded

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#130

All data

st_css() #IMPORTANT!

  censustract2000 <- as.factor(trimws(d[,"censustract2000"]))
  
  levels(censustract2000)[levels(censustract2000)=="999999"] <- "not_available.999999"

  new.d <- data.frame(new.d, censustract2000)
  new.d <- apply_labels(new.d, censustract2000 = "census_tract_2000")
  new.d.1 <- data.frame(new.d.1, censustract2000)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, censustract2000)
  summarytools::view(dfSummary(new.d$censustract2000, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	censustract2000 [labelled, factor]	census_tract_2000	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 599 ( 98.5% )		1559 (71.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 236 ( 99.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		173 (99.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2000 [factor]	1. 160800 2. 166700 3. 255200 4. 30501 5. 521900 6. 524800 7. 538900 8. 541000 9. 561900 10. not_available.999999	1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% )		9 (56.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CENSUS TRACT 2010

• Description: Identifies the patient’s census tract of residence at the time the tumor was diagnosed. Census Tract 2010 is a derived (geocoded) variables based on the Census Boundary files from 2010. See Census Tract 1970/80/90 [110]; Census Tract 2000 [130]; Census Tract 2020 [125]. Codes are those used by the U.S. Census Bureau for the Year 2010 Census. For consolidated records, the geocoded state should be based on the best address at diagnosis information identified.

• Rationale: Census tract codes allow central registries to calculate incidence rates for geographical areas having population estimates. This field allows a central registry to add Year 2020 Census tracts to tumors diagnosed in previous years, without losing the codes in data items [110], [130] and [135].

• The Census Bureau provides population and other demographic data for census tracts. This allows for small area analysis for general surveillance or special geographical and socioeconomic analysis.

• Instructions for Coding

  • This variable is generated through the process of geocoding either during abstracting or at the central registry level.
  • Census tract codes have a 4-digit basic number and also may have a 2-digit suffix. Census tract numbers range from 0001.00 to 9999.98, but the decimal should not be retained in the NAACCR layout.
  • It is recommended that all cases diagnosed through 2019 should have a geocoded Census Tract 2010.
  • At a minimum, all cases diagnosed through 2006-2019 should have a geocoded Census Tract 2010. Cases diagnosed 2006-2009 must have both State at DX Geocode 2000 [82] and State at DX Geocode 2010 [83] codes for proper assignment of the Census Tr Poverty Indicatr [145]. Cases diagnosed 2016-2019 must have both State at DX Geocode 2010 [83] and State at DX Geocode 2020 [84] codes for proper assignment of the Census Tr Poverty Indicatr [145].
  • If the patient has multiple tumors, geocoded state at diagnosis may be different for each tumor.
  • Do not update this item if the patient’s tract of residence changes. Store updated address information in the affiliated current address data items. Only update based on improved information on the residential address at time of diagnosis. For instance, it is appropriate to correct a tract during manual geocoding or a consolidation process.
  • PO Box address information should not be used to geocode this data item except in the infrequent case when no other address information is available.
  • Blank “Not geocoded” is allowable for cases diagnosed before 2005 and after 2019. However, it is preferred to have all cases geocoded to a 2010 Census Tract to allow for both retrospective and cross-sectional analyses.

• Codes

  • 000100-999998 Valid FIPS code
  • 000000 Area not census tracted
  • 999999 Area census tracted, but census tract is not available
  • Blank Census Tract 2010 not coded

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#135

All data

st_css() #IMPORTANT!

  censustract2010 <- as.factor(trimws(d[,"censustract2010"]))
  
  levels(censustract2010)[levels(censustract2010)=="999999"] <- "not_available.999999"

  new.d <- data.frame(new.d, censustract2010)
  new.d <- apply_labels(new.d, censustract2010 = "census_tract_2010")
  new.d.1 <- data.frame(new.d.1, censustract2010)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, censustract2010)
  summarytools::view(dfSummary(new.d$censustract2010, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	censustract2010 [labelled, factor]	census_tract_2010	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	7 ( 0.3% ) 3 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 3 ( 0.1% ) 3 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 4 ( 0.2% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 4 ( 0.2% ) 2 ( 0.1% ) 8 ( 0.4% ) 3 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 5 ( 0.2% ) 6 ( 0.3% ) 2 ( 0.1% ) 3 ( 0.1% ) 7 ( 0.3% ) 9 ( 0.4% ) 2 ( 0.1% ) 4 ( 0.2% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 4 ( 0.2% ) 1 ( 0.0% ) 3 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 6 ( 0.3% ) 5 ( 0.2% ) 2 ( 0.1% ) 6 ( 0.3% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 3 ( 0.1% ) 5 ( 0.2% ) 3 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 4 ( 0.2% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 3 ( 0.1% ) 3 ( 0.1% ) 1 ( 0.0% ) 5 ( 0.2% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 4 ( 0.2% ) 2 ( 0.1% ) 3 ( 0.1% ) 2 ( 0.1% ) 3 ( 0.1% ) 4 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 5 ( 0.2% ) 5 ( 0.2% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 4 ( 0.2% ) 1 ( 0.0% ) 2 ( 0.1% ) 1924 ( 88.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 186 ( 98.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 170 ( 97.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	1 ( 0.4% ) 2 ( 0.8% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 225 ( 94.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 278 ( 95.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	6 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 0.3% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 0 ( 0.0% ) 4 ( 0.4% ) 2 ( 0.2% ) 8 ( 0.7% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 5 ( 0.5% ) 5 ( 0.5% ) 1 ( 0.1% ) 3 ( 0.3% ) 7 ( 0.6% ) 8 ( 0.7% ) 2 ( 0.2% ) 4 ( 0.4% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 0.4% ) 0 ( 0.0% ) 3 ( 0.3% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 6 ( 0.6% ) 5 ( 0.5% ) 2 ( 0.2% ) 6 ( 0.6% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 4 ( 0.4% ) 3 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 0.3% ) 3 ( 0.3% ) 1 ( 0.1% ) 5 ( 0.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 2 ( 0.2% ) 3 ( 0.3% ) 2 ( 0.2% ) 3 ( 0.3% ) 3 ( 0.3% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 0 ( 0.0% ) 5 ( 0.5% ) 5 ( 0.5% ) 1 ( 0.1% ) 0 ( 0.0% ) 2 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 875 ( 80.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tract_2010 [factor]	1. 100 2. 1000 3. 10017 4. 10023 5. 1003 6. 100300 7. 100501 8. 100502 9. 100600 10. 100700 11. 100901 12. 100902 13. 100903 14. 10100 15. 10103 16. 10106 17. 10107 18. 10110 19. 102 20. 10200 21. 10203 22. 10204 23. 10205 24. 10206 25. 10208 26. 10300 27. 10301 28. 10302 29. 10303 30. 10304 31. 10400 32. 10401 33. 10402 34. 10403 35. 104101 36. 10416 37. 10422 38. 10500 39. 105000 40. 10501 41. 10502 42. 10504 43. 10507 44. 10508 45. 10510 46. 10511 47. 10512 48. 10513 49. 10514 50. 10515 51. 10516 52. 10600 53. 10601 54. 10602 55. 10603 56. 10604 57. 10605 58. 10607 59. 10608 60. 106403 61. 106646 62. 10700 63. 10701 64. 10702 65. 10703 66. 10706 67. 10707 68. 10708 69. 10709 70. 10710 71. 10712 72. 10800 73. 10801 74. 10802 75. 10803 76. 10806 77. 10807 78. 10808 79. 10900 80. 10903 81. 10904 82. 10906 83. 109800 84. 1100 85. 11000 86. 11003 87. 110115 88. 110200 89. 1103 90. 110300 91. 110301 92. 110400 93. 110503 94. 110505 95. 110601 96. 110700 97. 110900 98. 11100 99. 11102 100. 11105 [ 1242 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

MARITAL STATUS AT DX

• Description: Code for the patient’s marital status at the time of diagnosis for the reportable tumor. If the patient has multiple tumors, marital status may be different for each tumor.
• Rationale: Incidence and survival with certain cancers vary by marital status. The item also helps in patient identification.
• Codes
  • 1 Single (never married)
  • 2 Married (including common law)
  • 3 Separated
  • 4 Divorced
  • 5 Widowed
  • 6 Unmarried or Domestic Partner (same sex or opposite sex, registered or unregistered, other than common law marriage)
  • 9 Unknown
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#150

All data

st_css() #IMPORTANT!

  maritalstatusatdx <- as.factor(trimws(d[,"maritalstatusatdx"]))
  
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="1"] <- "Single.1"
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="2"] <- "Married.2"
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="3"] <- "Separated.3"
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="4"] <- "Divorced.4"
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="5"] <- "Widowed.5"
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="6"] <- "Unmarried_or_Domestic_Partner.6"
  levels(maritalstatusatdx)[levels(maritalstatusatdx)=="9"] <- "Unknown.9"


  new.d <- data.frame(new.d, maritalstatusatdx)
  new.d <- apply_labels(new.d, maritalstatusatdx = "marital_status_at_dx")
  new.d.1 <- data.frame(new.d.1, maritalstatusatdx)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, maritalstatusatdx)
  summarytools::view(dfSummary(new.d$maritalstatusatdx, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	maritalstatusatdx [labelled, factor]	marital_status_at_dx	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	399 ( 18.4% ) 1264 ( 58.3% ) 40 ( 1.8% ) 176 ( 8.1% ) 52 ( 2.4% ) 9 ( 0.4% ) 227 ( 10.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	53 ( 28.0% ) 98 ( 51.9% ) 5 ( 2.6% ) 17 ( 9.0% ) 4 ( 2.1% ) 1 ( 0.5% ) 11 ( 5.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	44 ( 25.3% ) 94 ( 54.0% ) 1 ( 0.6% ) 12 ( 6.9% ) 2 ( 1.1% ) 1 ( 0.6% ) 20 ( 11.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	40 ( 16.9% ) 149 ( 62.9% ) 2 ( 0.8% ) 13 ( 5.5% ) 4 ( 1.7% ) 4 ( 1.7% ) 25 ( 10.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	44 ( 25.3% ) 83 ( 47.7% ) 6 ( 3.4% ) 21 ( 12.1% ) 5 ( 2.9% ) 0 ( 0.0% ) 15 ( 8.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	60 ( 20.7% ) 170 ( 58.6% ) 5 ( 1.7% ) 25 ( 8.6% ) 7 ( 2.4% ) 0 ( 0.0% ) 23 ( 7.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	155 ( 14.3% ) 661 ( 60.8% ) 21 ( 1.9% ) 86 ( 7.9% ) 28 ( 2.6% ) 3 ( 0.3% ) 133 ( 12.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	marital_status_at_dx [factor]	1. Single.1 2. Married.2 3. Separated.3 4. Divorced.4 5. Widowed.5 6. Unmarried_or_Domestic_Par 7. Unknown.9	3 ( 18.8% ) 9 ( 56.2% ) 0 ( 0.0% ) 2 ( 12.5% ) 2 ( 12.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RACE 1

• Description: Code the patient’s race. Race is coded separately from Spanish/Hispanic Origin [190]. All tumors for the same patient should have the same race codes. If the patient is multiracial, code all races using RACE 2 through RACE 5 [161-164]. For coding instructions and race code history see the current SEER Program Coding and Staging Manual3.

• Reference to Census 2000 definitions for ethnicity and race: http://www.census.gov/prod/cen2000/doc/sf2.pdf (Appendix G).

• Rationale: Because race has a significant association with cancer rates and outcomes, a comparison between areas with different racial distributions may require an analysis of race to interpret the findings. The race codes listed correspond closely to race categories used by the U.S. Census Bureau to allow calculation of race-specific incidence rates. The full coding system should be used to allow accurate national comparison and collaboration, even if the state population does not include many of the race categories.

• Codes

  • 01 White
  • 02 Black

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#160

All data

st_css() #IMPORTANT!

  race1 <- as.factor(trimws(d[,"race1"]))
  
  levels(race1)[levels(race1)=="1"] <- "White.1"
  levels(race1)[levels(race1)=="2"] <- "Black.2"
  
  new.d <- data.frame(new.d, race1)
  new.d <- apply_labels(new.d, race1 = "race_1")
  new.d.1 <- data.frame(new.d.1, race1)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, race1)
  summarytools::view(dfSummary(new.d$race1, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [labelled, factor]	race_1	1. White.1 2. Black.2	1 ( 0.0% ) 2166 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	1 ( 0.1% ) 1086 ( 99.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race1 [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RACE 2

-Description: Code the patient’s race. Race is coded separately from Spanish/Hispanic Origin [190]. All tumors for the same patient should have the same race codes. If the patient is multiracial, code all races using RACE 2 through RACE 5 [161-164]. For coding instructions and race code history see the current SEER Program Coding and Staging Manual3.

-Reference to Census 2000 definitions for ethnicity and race: http://www.census.gov/prod/cen2000/doc/sf2.pdf (Appendix G). -Rationale: Because race has a significant association with cancer rates and outcomes, a comparison between areas with different racial distributions may require an analysis of race to interpret the findings. The race codes listed correspond closely to race categories used by the U.S. Census Bureau to allow calculation of race-specific incidence rates. The full coding system should be used to allow accurate national comparison and collaboration, even if the state population does not include many of the race categories. - Codes + 01 White + 02 Black + 88 No further race documented

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#161

All data

st_css() #IMPORTANT!

  race2 <- as.factor(trimws(d[,"race2"]))
  
  levels(race2)[levels(race2)=="1"] <- "White.1"
  levels(race2)[levels(race2)=="88"] <- "No_further_race.88"
  
  new.d <- data.frame(new.d, race2)
  new.d <- apply_labels(new.d, race2 = "race_2")
  new.d.1 <- data.frame(new.d.1, race2)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, race2)
  summarytools::view(dfSummary(new.d$race2, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [labelled, factor]	race_2	1. White.1 2. No_further_race.88	13 ( 0.6% ) 2154 ( 99.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	3 ( 1.6% ) 186 ( 98.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	8 ( 4.6% ) 166 ( 95.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	2 ( 0.8% ) 235 ( 99.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	0 ( 0.0% ) 290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	0 ( 0.0% ) 1087 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race2 [factor]	1. White.1 2. No_further_race.88	0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RACE 3

• Description: Code the patient’s race. Race is coded separately from Spanish/Hispanic Origin [190]. All tumors for the same patient should have the same race codes. If the patient is multiracial, code all races using RACE 2 through RACE 5 [161-164]. For coding instructions and race code history see the current SEER Program Coding and Staging Manual3.

• Reference to Census 2000 definitions for ethnicity and race: http://www.census.gov/prod/cen2000/doc/sf2.pdf (Appendix G).

• Rationale： Because race has a significant association with cancer rates and outcomes, a comparison between areas with different racial distributions may require an analysis of race to interpret the findings. The race codes listed correspond closely to race categories used by the U.S. Census Bureau to allow calculation of race-specific incidence rates. The full coding system should be used to allow accurate national comparison and collaboration, even if the state population does not include many of the race categories.

• Codes

  • 01 White
  • 02 Black
  • 88 No further race documented

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#162

All data

st_css() #IMPORTANT!

  race3 <- as.factor(trimws(d[,"race3"]))
  
  levels(race3)[levels(race3)=="1"] <- "White.1"
  levels(race3)[levels(race3)=="88"] <- "No_further_race.88"
  
  new.d <- data.frame(new.d, race3)
  new.d <- apply_labels(new.d, race3 = "race_3")
  new.d.1 <- data.frame(new.d.1, race3)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, race3)
  summarytools::view(dfSummary(new.d$race3, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [labelled, factor]	race_3	1. No_further_race.88	2167 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	1087 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race3 [factor]	1. No_further_race.88	16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RACE 4

• Description: Code the patient’s race. Race is coded separately from Spanish/Hispanic Origin [190]. All tumors for the same patient should have the same race codes. If the patient is multiracial, code all races using RACE 2 through RACE 5 [161-164]. For coding instructions and race code history see the current SEER Program Coding and Staging Manual3.

• Reference to Census 2000 definitions for ethnicity and race: http://www.census.gov/prod/cen2000/doc/sf2.pdf (Appendix G).

• Rationale: Because race has a significant association with cancer rates and outcomes, a comparison between areas with different racial distributions may require an analysis of race to interpret the findings. The race codes listed correspond closely to race categories used by the U.S. Census Bureau to allow calculation of race-specific incidence rates. The full coding system should be used to allow accurate national comparison and collaboration, even if the state population does not include many of the race categories.

• Codes

  • 01 White
  • 02 Black
  • 88 No further race documented

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#163

All data

st_css() #IMPORTANT!

  race4 <- as.factor(trimws(d[,"race4"]))
  
  levels(race4)[levels(race4)=="1"] <- "White.1"
  levels(race4)[levels(race4)=="88"] <- "No_further_race.88"
  
  new.d <- data.frame(new.d, race4)
  new.d <- apply_labels(new.d, race4 = "race_4")
  new.d.1 <- data.frame(new.d.1, race4)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, race4)
  summarytools::view(dfSummary(new.d$race4, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [labelled, factor]	race_4	1. No_further_race.88	2167 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	1087 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race4 [factor]	1. No_further_race.88	16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RACE 5

• Description: Code the patient’s race. Race is coded separately from Spanish/Hispanic Origin [190]. All tumors for the same patient should have the same race codes. If the patient is multiracial, code all races using RACE 2 through RACE 5 [161-164]. For coding instructions and race code history see the current SEER Program Coding and Staging Manual3.

• Reference to Census 2000 definitions for ethnicity and race: http://www.census.gov/prod/cen2000/doc/sf2.pdf (Appendix G).

• Rationale: Because race has a significant association with cancer rates and outcomes, a comparison between areas with different racial distributions may require an analysis of race to interpret the findings. The race codes listed correspond closely to race categories used by the U.S. Census Bureau to allow calculation of race-specific incidence rates. The full coding system should be used to allow accurate national comparison and collaboration, even if the state population does not include many of the race categories.

• Codes

  • 01 White
  • 02 Black
  • 88 No further race documented

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#164

All data

st_css() #IMPORTANT!

  race5 <- as.factor(trimws(d[,"race5"]))
  
  levels(race5)[levels(race5)=="1"] <- "White.1"
  levels(race5)[levels(race5)=="88"] <- "No_further_race.88"
  
  new.d <- data.frame(new.d, race5)
  new.d <- apply_labels(new.d, race5 = "race_5")
  new.d.1 <- data.frame(new.d.1, race5)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, race5)
  summarytools::view(dfSummary(new.d$race5, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [labelled, factor]	race_5	1. No_further_race.88	2167 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	1087 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race5 [factor]	1. No_further_race.88	16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SPANISH/HISPANIC ORIGIN

• Description: Code identifying persons of Spanish or Hispanic origin. This code is used by hospital and central registries to show the “best guess” as to whether or not the person should be classified as Hispanic for purposes of calculating cancer rates. If the patient has multiple tumors, all records should have the same code.
• Reference to Census 2000 definitions for ethnicity and race: http://www.census.gov/prod/cen2000/doc/sf2.pdf. All information resources should be used to determine the correct code, including:
  • Stated ethnicity in the medical record
  • Stated Hispanic origin on the death certificate
  • Birthplace
  • Information about life history and/or language spoken found during the abstracting process
  • Patient’s last name [2230] or maiden name [2390] found on a list of Hispanic names
• Some registries code the information from the medical record, others code ethnicity based on Spanish names, and others use a combination of methods.
• Persons of Spanish or Hispanic origin may be of any race, but these categories generally are not used for Native Americans, Filipinos, etc., who may have Spanish names. If a patient has an Hispanic name, but there is reason to believe they are not Hispanic (e.g., the patient is Filipino, or the patient is a woman known to be non-Hispanic who has a Hispanic married name), the code in this field should be 0 (non-Spanish, non-Hispanic). The code in item Computed Ethnicity [200], however, would reflect the Hispanic name.
• Assign code 7 if Hispanic ethnicity is based strictly on a computer list or algorithm (unless contrary evidence is available) and also code in Computed Ethnicity [200].
• Rationale: See the rationales for the Race 1-5 [160-164] and Computed Ethnicity [200]. Ethnic origin has a significant association with cancer rates and outcomes. Hispanic populations have different patterns of occurrence of cancer from other populations that may be included in the “white” category of Race [160].
• Codes
  • 0 Non-Spanish; non-Hispanic
  • 1 Mexican (includes Chicano)
  • 2 Puerto Rican
  • 3 Cuban
  • 4 South or Central American (except Brazil)
  • 5 Other specified Spanish/Hispanic origin (includes European; excludes Dominican Republic)
  • 6 Spanish, NOS Hispanic, NOS Latino, NOS There is evidence, other than surname or maiden name, that the person is Hispanic, but he/she cannot be assigned to any of the other categories 1-5.
  • 7 Spanish surname only (Code 7 is ordinarily for central registry use only, hospital registrars may use code 7 if using a list of Hispanic surnames provided by their central registry; otherwise, code 9 ‘unknown whether Spanish or not’ should be used.) The only evidence of the person’s Hispanic origin is the surname or maiden name and there is no contrary evidence that the person is not Hispanic.
  • 8 Dominican Republic
  • 9 Unknown whether Spanish or not
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#190

All data

st_css() #IMPORTANT!

  spanishhispanicorigin <- as.factor(trimws(d[,"spanishhispanicorigin"]))
  
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="0"] <- "Non_Spanish_Hispanic.0"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="1"] <- "Mexican.1"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="2"] <- "Puerto_Rican.2"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="3"] <- "Cuban.3"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="4"] <- "South_or_Central_American.4)"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="5"] <- "Other_specified.5"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="6"] <- "Spanish_Hispanic_Latino_NOS.6"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="7"] <- "Spanish_surname_only.7"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="8"] <- "Dominican_Republic.8"
  levels(spanishhispanicorigin)[levels(spanishhispanicorigin)=="9"] <- "Unknown.9"

  new.d <- data.frame(new.d, spanishhispanicorigin)
  new.d <- apply_labels(new.d, spanishhispanicorigin = "spanish_hispanic_origin")
  new.d.1 <- data.frame(new.d.1, spanishhispanicorigin)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, spanishhispanicorigin)
  summarytools::view(dfSummary(new.d$spanishhispanicorigin, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanishhispanicorigin [labelled, factor]	spanish_hispanic_origin	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	2145 ( 99.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 6 ( 0.3% ) 2 ( 0.1% ) 10 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	187 ( 98.9% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	172 ( 98.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	235 ( 99.2% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	173 ( 99.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	283 ( 97.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 6 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	1079 ( 99.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 4 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	spanish_hispanic_origin [factor]	1. Non_Spanish_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. Dominican_Republic.8 7. Unknown.9	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

NHIA DERIVED HISP ORIGIN

• Description: The NAACCR Hispanic Identification Algorithm (NHIA) uses a combination of standard variables to directly or indirectly classify cases as Hispanic for analytic purposes. It is possible to separate Hispanic ancestral subgroups (e.g., Mexican) when indirect assignment results from birthplace information but not from surname match. The algorithm uses the following standard variables: Spanish/Hispanic Origin [190], Name–Last [2230], Name–Maiden [2390], Birthplace [250], Race 1 [160], IHS Link [192], and Sex [220].

• Code 7 (Spanish surname only) of the Spanish/Hispanic Origin [190] data item became effective with 1994 diagnoses. It is recommended that NHIA should be run on 1995 and later diagnoses. However, a central registry may run it on their data for prior years. For greater detail, please refer to the technical documentation: http://www.naaccr.org/LinkClick.aspx?fileticket=6E20OT41TcA%3d&tabid=118&mid=458.

• Rationale: Sometimes despite best efforts to obtain complete information directly from the medical record, information is not available and is reported to the cancer registry as a missing data item. With regard to Hispanic ethnicity, some cancer registries have found it necessary to rely on indirect methods to populate this data element. Registries often have significant numbers or proportions of Hispanic populations in their jurisdiction.

• Codes

  • 0 Non-Hispanic
  • 1 Mexican, by birthplace or other specific identifier
  • 2 Puerto Rican, by birthplace or other specific identifier
  • 3 Cuban, by birthplace or other specific identifier
  • 4 South or Central American (except Brazil), by birthplace or other specific identifier
  • 5 Other specified Spanish/Hispanic origin (includes European; excludes Dominican Republic), by birthplace or other specific identifier
  • 6 Spanish, NOS; Hispanic, NOS; Latino, NOS
  • 7 NHIA surname match only
  • 8 Dominican Republic
  • Blank Algorithm has not been run

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#191

All data

st_css() #IMPORTANT!

  nhiaderivedhisporigin <- as.factor(trimws(d[,"nhiaderivedhisporigin"]))
  
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="0"] <- "Non_Hispanic.0"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="1"] <- "Mexican.1"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="2"] <- "Puerto_Rican.2"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="3"] <- "Cuban.3"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="4"] <- "South_or_Central_American.4)"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="5"] <- "Other_specified.5"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="6"] <- "Spanish_Hispanic_Latino_NOS.6"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="7"] <- "NHIA_surname_match.7"
  levels(nhiaderivedhisporigin)[levels(nhiaderivedhisporigin)=="8"] <- "Dominican_Republic.8"

  new.d <- data.frame(new.d, nhiaderivedhisporigin)
  new.d <- apply_labels(new.d, nhiaderivedhisporigin = "nhia_derived_hisp_origin")
  new.d.1 <- data.frame(new.d.1, nhiaderivedhisporigin)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, nhiaderivedhisporigin)
  summarytools::view(dfSummary(new.d$nhiaderivedhisporigin, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhiaderivedhisporigin [labelled, factor]	nhia_derived_hisp_origin	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	2152 ( 99.3% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 6 ( 0.3% ) 2 ( 0.1% ) 2 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	186 ( 98.4% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	171 ( 98.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	235 ( 99.2% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	173 ( 99.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	289 ( 99.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	1082 ( 99.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	nhia_derived_hisp_origin [factor]	1. Non_Hispanic.0 2. Cuban.3 3. South_or_Central_American 4. Other_specified.5 5. Spanish_Hispanic_Latino_N 6. NHIA_surname_match.7 7. Dominican_Republic.8	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

IHS LINK

• Description: This variable captures the results of the linkage of the registry database with the Indian Health Service patient registration database.
• Rationale: The IHS linkage identifies cancer cases among American Indians who were misclassified as non-Indian in the registry database in order to improve the quality of cancer surveillance data on American Indians in individual registries and in all registries as a whole. The goal is to include cancer incidence data for American Indians in the United States Cancer Statistics by use of this variable as well as the race variable.
• Codes
  • 0 Record sent for linkage, no IHS match
  • 1 Record sent for linkage, IHS match
  • Blank Record not sent for linkage or linkage result pending
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#192

All data

st_css() #IMPORTANT!

  ihslink <- as.factor(trimws(d[,"ihslink"]))
  
  levels(ihslink)[levels(ihslink)=="0"] <- "no_IHS_match.0"
  levels(ihslink)[levels(ihslink)=="1"] <- "IHS_match.1"

  new.d <- data.frame(new.d, ihslink)
  new.d <- apply_labels(new.d, ihslink = "ihs_link")
  new.d.1 <- data.frame(new.d.1, ihslink)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, ihslink)
  summarytools::view(dfSummary(new.d$ihslink, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihslink [labelled, factor]	ihs_link	1. no_IHS_match.0 2. IHS_match.1	1398 ( 99.9% ) 1 ( 0.1% )		768 (35.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	5 ( 100.0% ) 0 ( 0.0% )		184 (97.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	5 ( 83.3% ) 1 ( 16.7% )		168 (96.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	8 ( 100.0% ) 0 ( 0.0% )		229 (96.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	6 ( 100.0% ) 0 ( 0.0% )		168 (96.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	290 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	1084 ( 100.0% ) 0 ( 0.0% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ihs_link [factor]	1. no_IHS_match.0 2. IHS_match.1	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RACE–NAPIIA(DERIVED API)

• Description: NAPIIA is an acronym for NAACCR Asian and Pacific Islander Identification Algorithm. Race–NAPIIA(derived API) recodes some single-race cases with a Race 1 [160] code of 96 to a more specific Asian race category, based on an algorithm that makes use of the birthplace and name fields (first, last, and maiden names). For single-race cases with a Race 1 code other than 96, it returns the Race 1 code. Multiple-race cases (those with information in Race 2 through Race 5, [161-164]) are handled variously; for greater detail please refer to the technical documentation: http://www.naaccr.org/LinkClick.aspx?fileticket=3HnBhlmhkBs%3d&tabid=118&mid=458

• In Version 1.1 of the algorithm, birthplace can be used to indirectly assign a specific race to one of eight Asian race groups (Chinese, Japanese, Vietnamese, Korean, Asian Indian, Filipino, Thai, and Cambodian), and names can be used to indirectly assign a specific race to one of seven Asian groups (Chinese, Japanese, Vietnamese, Korean, Asian Indian, Filipino, and Hmong). Subsequent versions of NAPIIA may incorporate Pacific Islanders and may potentially incorporate name lists for Thai, Cambodian, and Laotians.

• Rationale: The use of more specific Asian and Pacific Islander codes will enhance surveillance and research activities focused on specific API subgroups.

• Codes

  • 01 White
  • 02 Black

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#193

All data

st_css() #IMPORTANT!

  racenapiia <- as.factor(trimws(d[,"racenapiia"]))
  
  levels(racenapiia)[levels(racenapiia)=="1"] <- "White.1"
  levels(racenapiia)[levels(racenapiia)=="2"] <- "Black.2"

  new.d <- data.frame(new.d, racenapiia)
  new.d <- apply_labels(new.d, racenapiia = "race_napiia")
  new.d.1 <- data.frame(new.d.1, racenapiia)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, racenapiia)
  summarytools::view(dfSummary(new.d$racenapiia, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	racenapiia [labelled, factor]	race_napiia	1. White.1 2. Black.2	1 ( 0.0% ) 2166 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	1 ( 0.1% ) 1086 ( 99.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	race_napiia [factor]	1. White.1 2. Black.2	0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SEX

• Description: Code for the sex of the patient.
• Codes
  • 1 Male
  • 2 Female
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#220

All data

st_css() #IMPORTANT!

  sex <- as.factor(trimws(d[,"sex"]))
  
  levels(sex)[levels(sex)=="1"] <- "Male.1"
  levels(sex)[levels(sex)=="2"] <- "Female.2"

  new.d <- data.frame(new.d, sex)
  new.d <- apply_labels(new.d, sex = "sex")
  new.d.1 <- data.frame(new.d.1, sex)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, sex)
  summarytools::view(dfSummary(new.d$sex, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [labelled, factor]	sex	1. Male.1 2. Female.2	2166 ( 100.0% ) 1 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	189 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	174 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	237 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	174 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	290 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	1086 ( 99.9% ) 1 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sex [factor]	1. Male.1 2. Female.2	16 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AGE AT DIAGNOSIS

• Description: Age of the patient at diagnosis in complete years. Different tumors for the same patient may have different values.
• Codes
  • 000 Less than 1 year old; diagnosed in utero
  • 001 1 year old, but less than 2 years
  • 002 2 years old …
  • 101 101 years old …
  • 120 120 years old
  • 999 Unknown age
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#230

All data

st_css() #IMPORTANT!

  ageatdiagnosis <- as.factor(trimws(d[,"ageatdiagnosis"]))
  
  new.d <- data.frame(new.d, ageatdiagnosis)
  new.d <- apply_labels(new.d, ageatdiagnosis = "age_at_diagnosis")
  new.d.1 <- data.frame(new.d.1, ageatdiagnosis)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, ageatdiagnosis)
  summarytools::view(dfSummary(new.d$ageatdiagnosis, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ageatdiagnosis [labelled, factor]	age_at_diagnosis	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 6 ( 0.3% ) 8 ( 0.4% ) 8 ( 0.4% ) 16 ( 0.7% ) 14 ( 0.6% ) 22 ( 1.0% ) 28 ( 1.3% ) 36 ( 1.7% ) 51 ( 2.4% ) 45 ( 2.1% ) 61 ( 2.8% ) 79 ( 3.6% ) 81 ( 3.7% ) 74 ( 3.4% ) 94 ( 4.3% ) 122 ( 5.6% ) 116 ( 5.4% ) 106 ( 4.9% ) 108 ( 5.0% ) 104 ( 4.8% ) 110 ( 5.1% ) 142 ( 6.6% ) 140 ( 6.5% ) 117 ( 5.4% ) 96 ( 4.4% ) 99 ( 4.6% ) 66 ( 3.0% ) 54 ( 2.5% ) 55 ( 2.5% ) 46 ( 2.1% ) 42 ( 1.9% ) 3 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 4 ( 0.2% ) 1 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 7 ( 3.7% ) 0 ( 0.0% ) 4 ( 2.1% ) 2 ( 1.1% ) 5 ( 2.6% ) 1 ( 0.5% ) 7 ( 3.7% ) 9 ( 4.8% ) 7 ( 3.7% ) 6 ( 3.2% ) 5 ( 2.6% ) 17 ( 9.0% ) 13 ( 6.9% ) 9 ( 4.8% ) 10 ( 5.3% ) 8 ( 4.2% ) 15 ( 7.9% ) 13 ( 6.9% ) 3 ( 1.6% ) 7 ( 3.7% ) 13 ( 6.9% ) 6 ( 3.2% ) 4 ( 2.1% ) 5 ( 2.6% ) 5 ( 2.6% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.6% ) 3 ( 1.7% ) 1 ( 0.6% ) 4 ( 2.3% ) 2 ( 1.1% ) 2 ( 1.1% ) 3 ( 1.7% ) 4 ( 2.3% ) 6 ( 3.4% ) 11 ( 6.3% ) 7 ( 4.0% ) 10 ( 5.7% ) 7 ( 4.0% ) 9 ( 5.2% ) 6 ( 3.4% ) 7 ( 4.0% ) 13 ( 7.5% ) 10 ( 5.7% ) 12 ( 6.9% ) 10 ( 5.7% ) 11 ( 6.3% ) 9 ( 5.2% ) 3 ( 1.7% ) 3 ( 1.7% ) 6 ( 3.4% ) 3 ( 1.7% ) 4 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.3% ) 1 ( 0.4% ) 1 ( 0.4% ) 4 ( 1.7% ) 6 ( 2.5% ) 10 ( 4.2% ) 7 ( 3.0% ) 7 ( 3.0% ) 13 ( 5.5% ) 10 ( 4.2% ) 9 ( 3.8% ) 6 ( 2.5% ) 18 ( 7.6% ) 15 ( 6.3% ) 8 ( 3.4% ) 14 ( 5.9% ) 9 ( 3.8% ) 10 ( 4.2% ) 13 ( 5.5% ) 16 ( 6.8% ) 8 ( 3.4% ) 7 ( 3.0% ) 12 ( 5.1% ) 10 ( 4.2% ) 7 ( 3.0% ) 4 ( 1.7% ) 3 ( 1.3% ) 4 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 3 ( 1.7% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 3 ( 1.7% ) 3 ( 1.7% ) 2 ( 1.1% ) 5 ( 2.9% ) 3 ( 1.7% ) 6 ( 3.4% ) 6 ( 3.4% ) 9 ( 5.2% ) 4 ( 2.3% ) 12 ( 6.9% ) 14 ( 8.0% ) 11 ( 6.3% ) 12 ( 6.9% ) 7 ( 4.0% ) 5 ( 2.9% ) 6 ( 3.4% ) 4 ( 2.3% ) 4 ( 2.3% ) 9 ( 5.2% ) 8 ( 4.6% ) 4 ( 2.3% ) 6 ( 3.4% ) 4 ( 2.3% ) 7 ( 4.0% ) 2 ( 1.1% ) 4 ( 2.3% ) 2 ( 1.1% ) 0 ( 0.0% ) 3 ( 1.7% ) 2 ( 1.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 3 ( 1.0% ) 3 ( 1.0% ) 2 ( 0.7% ) 4 ( 1.4% ) 3 ( 1.0% ) 10 ( 3.4% ) 7 ( 2.4% ) 8 ( 2.8% ) 13 ( 4.5% ) 13 ( 4.5% ) 5 ( 1.7% ) 11 ( 3.8% ) 19 ( 6.6% ) 14 ( 4.8% ) 15 ( 5.2% ) 19 ( 6.6% ) 15 ( 5.2% ) 12 ( 4.1% ) 25 ( 8.6% ) 14 ( 4.8% ) 18 ( 6.2% ) 9 ( 3.1% ) 11 ( 3.8% ) 7 ( 2.4% ) 8 ( 2.8% ) 7 ( 2.4% ) 4 ( 1.4% ) 9 ( 3.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 4 ( 0.4% ) 2 ( 0.2% ) 4 ( 0.4% ) 7 ( 0.6% ) 8 ( 0.7% ) 6 ( 0.6% ) 16 ( 1.5% ) 17 ( 1.6% ) 21 ( 1.9% ) 20 ( 1.8% ) 35 ( 3.2% ) 35 ( 3.2% ) 32 ( 2.9% ) 38 ( 3.5% ) 50 ( 4.6% ) 54 ( 5.0% ) 52 ( 4.8% ) 49 ( 4.5% ) 52 ( 4.8% ) 57 ( 5.2% ) 60 ( 5.5% ) 74 ( 6.8% ) 81 ( 7.5% ) 68 ( 6.3% ) 54 ( 5.0% ) 50 ( 4.6% ) 34 ( 3.1% ) 28 ( 2.6% ) 26 ( 2.4% ) 29 ( 2.7% ) 19 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	age_at_diagnosis [factor]	1. 26 2. 38 3. 40 4. 41 5. 42 6. 43 7. 44 8. 45 9. 46 10. 47 11. 48 12. 49 13. 50 14. 51 15. 52 16. 53 17. 54 18. 55 19. 56 20. 57 21. 58 22. 59 23. 60 24. 61 25. 62 26. 63 27. 64 28. 65 29. 66 30. 67 31. 68 32. 69 33. 70 34. 71 35. 72 36. 73 37. 74 38. 75 39. 76 40. 77 41. 78 42. 79	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 2 ( 12.5% ) 0 ( 0.0% ) 2 ( 12.5% ) 2 ( 12.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DATE OF BIRTH

• Description: Date of birth of the patient. See Chapter X for date format. If age at diagnosis and year of diagnosis are known, but year of birth is unknown, then year of birth should be calculated and so coded. Only the year should be entered, left-justified. Estimate date of birth when information is not available. It is better to estimate than to leave birth date unknown.

• date var

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#240

All data

st_css() #IMPORTANT!

  dateofbirth <- trimws(d[,"dateofbirth"])

  new.d <- data.frame(new.d, dateofbirth)
  new.d <- apply_labels(new.d, dateofbirth = "date_of_birth")
  #new.d.1 <- data.frame(new.d.1, dateofbirth)
  
  #Using kable function to form a nice table
  temp.d <- data.frame (new.d.1, dateofbirth)
  summarytools::view(dfSummary(new.d$dateofbirth, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	dateofbirth [labelled, character]	date_of_birth	1. 195012 2. 195405 3. 195411 4. 19550799 5. 194701 6. 194901 7. 194908 8. 19490904 9. 194911 10. 19500117 11. 195105 12. 195201 13. 195202 14. 195308 15. 195408 16. 195412 17. 19560199 18. 195605 19. 19570999 20. 196003 21. 196106 22. 196207 23. 194206 24. 19430499 25. 194312 26. 194508 27. 19461031 28. 194702 29. 194811 30. 19490415 31. 194905 32. 19490699 33. 19490999 34. 194910 35. 195001 36. 195002 37. 195005 38. 19500629 39. 195007 40. 195009 41. 195101 42. 195110 43. 19520899 44. 195307 45. 19530728 46. 195310 47. 19531204 48. 195406 49. 195410 50. 195509 51. 195511 52. 195603 53. 19570129 54. 195708 55. 19580999 56. 195810 57. 195901 58. 196006 59. 196007 60. 196008 61. 19600899 62. 196011 63. 196012 64. 19410519 65. 19410521 66. 194106 67. 19410806 68. 194201 69. 19420224 70. 19420330 71. 19420607 72. 194208 73. 19421201 74. 194303 75. 19431009 76. 19440531 77. 19440712 78. 194408 79. 19441212 80. 194501 81. 194504 82. 194506 83. 19450824 84. 194509 85. 194511 86. 19451128 87. 194601 88. 19460129 89. 19460227 90. 194606 91. 194607 92. 19460729 93. 194609 94. 19460910 95. 194610 96. 194611 97. 19461105 98. 19461121 99. 194612 100. 19470299 [ 1685 others ]	5 ( 0.2% ) 5 ( 0.2% ) 5 ( 0.2% ) 5 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 4 ( 0.2% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 3 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 1878 ( 86.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 195201 2. 195012 3. 195310 4. 195408 5. 195411 6. 195509 7. 194201 8. 194206 9. 194303 10. 194408 11. 194511 12. 194606 13. 194610 14. 194612 15. 194702 16. 194703 17. 194805 18. 194901 19. 194908 20. 194910 21. 195002 22. 195004 23. 195005 24. 195007 25. 195101 26. 195105 27. 195203 28. 195405 29. 195412 30. 195504 31. 195603 32. 195608 33. 195609 34. 195806 35. 195807 36. 195901 37. 196003 38. 196102 39. 196106 40. 196306 41. 196510 42. 196605 43. 193909 44. 194012 45. 194204 46. 194209 47. 194308 48. 194312 49. 194401 50. 194403 [ 90 others ]	4 ( 2.1% ) 3 ( 1.6% ) 3 ( 1.6% ) 3 ( 1.6% ) 3 ( 1.6% ) 3 ( 1.6% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 90 ( 47.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 19520317 2. 19580103 3. 19370416 4. 19380429 5. 19410710 6. 19411231 7. 19420224 8. 19420414 9. 19420807 10. 19420913 11. 19421122 12. 19421201 13. 19421223 14. 19421231 15. 19430525 16. 19431111 17. 19431119 18. 19440124 19. 19440223 20. 19440512 21. 19450529 22. 19450617 23. 19451025 24. 19451106 25. 19451119 26. 19460307 27. 19460506 28. 19460705 29. 19460821 30. 19460918 31. 19461014 32. 19461121 33. 19461209 34. 19470207 35. 19470321 36. 19470508 37. 19470610 38. 19470701 39. 19470914 40. 19471003 41. 19471019 42. 19471023 43. 19471208 44. 19471221 45. 19480402 46. 19480506 47. 19480615 48. 19480818 49. 19481123 50. 19481213 [ 122 others ]	2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 122 ( 70.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 194701 2. 194911 3. 195202 4. 195308 5. 195405 6. 195511 7. 195605 8. 196007 9. 196011 10. 196207 11. 194106 12. 194208 13. 194312 14. 194506 15. 194508 16. 194509 17. 194607 18. 194609 19. 194706 20. 194710 21. 194802 22. 194807 23. 194811 24. 194901 25. 194905 26. 194908 27. 194909 28. 195001 29. 195003 30. 195009 31. 195012 32. 195105 33. 195106 34. 195107 35. 195108 36. 195110 37. 195303 38. 195307 39. 195402 40. 195406 41. 195410 42. 195411 43. 195412 44. 195505 45. 195606 46. 195702 47. 195705 48. 195708 49. 195711 50. 195810 [ 114 others ]	3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 3 ( 1.3% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 127 ( 53.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 19550799 2. 19570999 3. 19430499 4. 19490999 5. 19520899 6. 19560199 7. 19580999 8. 19600899 9. 19470299 10. 19480499 11. 19490699 12. 19490799 13. 19500699 14. 19540199 15. 19540699 16. 19540999 17. 19550199 18. 19550899 19. 19551299 20. 19560399 21. 19561199 22. 19570399 23. 19580299 24. 19581299 25. 19601099 26. 19610899 27. 19631099 28. 19641099 29. 19390599 30. 19390899 31. 19400699 32. 19401299 33. 19410799 34. 19410899 35. 19420899 36. 19430199 37. 19430399 38. 19430699 39. 19430799 40. 19431299 41. 19440299 42. 19440499 43. 19440699 44. 19440899 45. 19440999 46. 19450199 47. 19450299 48. 19450599 49. 19450699 50. 19451099 [ 86 others ]	4 ( 2.3% ) 4 ( 2.3% ) 3 ( 1.7% ) 3 ( 1.7% ) 3 ( 1.7% ) 3 ( 1.7% ) 3 ( 1.7% ) 3 ( 1.7% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 86 ( 49.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 19491227 2. 19500924 3. 19510617 4. 19531002 5. 19551108 6. 19591227 7. 19401108 8. 19401209 9. 19410407 10. 19410521 11. 19410614 12. 19410704 13. 19410716 14. 19411002 15. 19411013 16. 19411212 17. 19420723 18. 19421208 19. 19430110 20. 19430124 21. 19430516 22. 19430705 23. 19430804 24. 19431103 25. 19440424 26. 19440615 27. 19440626 28. 19440719 29. 19440918 30. 19440925 31. 19441014 32. 19441228 33. 19450118 34. 19450319 35. 19450502 36. 19450630 37. 19450714 38. 19450820 39. 19450824 40. 19450921 41. 19451016 42. 19451105 43. 19451204 44. 19451226 45. 19460129 46. 19460131 47. 19460227 48. 19460309 49. 19460620 50. 19460802 [ 234 others ]	2 ( 0.7% ) 2 ( 0.7% ) 2 ( 0.7% ) 2 ( 0.7% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 234 ( 80.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 19461031 2. 19490904 3. 19500117 4. 19410519 5. 19410806 6. 19420330 7. 19420607 8. 19431009 9. 19440531 10. 19440712 11. 19441212 12. 19451128 13. 19460729 14. 19460910 15. 19461105 16. 19470613 17. 19480104 18. 19480310 19. 19480403 20. 19480519 21. 19480709 22. 19480812 23. 19480915 24. 19481230 25. 19490221 26. 19490415 27. 19490504 28. 19490623 29. 19490802 30. 19490805 31. 19500102 32. 19500308 33. 19500607 34. 19500629 35. 19501218 36. 19510212 37. 19510303 38. 19510408 39. 19510508 40. 19510813 41. 19520118 42. 19520225 43. 19520314 44. 19520716 45. 19521012 46. 19530821 47. 19531204 48. 19540208 49. 19540510 50. 19540531 [ 965 others ]	3 ( 0.3% ) 3 ( 0.3% ) 3 ( 0.3% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 984 ( 90.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_birth [character]	1. 19450499 2. 19480999 3. 19490299 4. 19490699 5. 19501299 6. 19520499 7. 19530899 8. 19540299 9. 19550799 10. 19560199 11. 19561099 12. 19561299 13. 19591099 14. 19600599 15. 19620499 16. 19660799	1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

BIRTHPLACE

• Description: Code for place of birth of the patient. If a patient has multiple tumors, all records should contain the same code.

• Rationale: Place of Birth is helpful for patient matching and can be used when reviewing race and ethnicity. In addition, adding birthplace data to race and ethnicity allows for a more specific definition of the population being reported. Careful descriptions of ancestry, birthplace, and immigration history of populations studied are needed to make the basis for classification into ethnic groups clear. Birthplace has been associated with variation in genetic, socioeconomic, cultural, and nutritional characteristics that affect patterns of disease. A better understanding of the differences within racial and ethnic categories also can help states develop effective, culturally sensitive public health prevention programs to decrease the prevalence of high-risk behaviors and increase the use of preventive services.

• Note: For cases diagnosed January 1, 2013, and later, Birthplace–State [252] and Birthplace–Country [254] replace Birthplace [250].

• Codes: See Appendix B for numeric and alphabetic lists of places and codes (also see Appendix B of the SEER Program Code Manual at seer.cancer.gov/tools/codingmanuals/index.html).

• Many numeric codes need to be identified!

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#250

All data

st_css() #IMPORTANT!

  birthplace <- as.factor(trimws(d[,"birthplace"]))
  # recode for interpretable birthplace
  #new.d.n <- data.frame(new.d.n, birthplace) # keep NAACCR coding
  levels(birthplace)[levels(birthplace)=="999"] <- "Unkown.999"
  levels(birthplace)[levels(birthplace)=="97"] <- "Sonoma (Greater California).97"
  levels(birthplace)[levels(birthplace)=="75"] <- "Kiowa.75"
  levels(birthplace)[levels(birthplace)=="73"] <- "Ouachita.73"
  levels(birthplace)[levels(birthplace)=="5"] <- "Bristol.5"
  levels(birthplace)[levels(birthplace)=="33"] <- "Burke.33"
  levels(birthplace)[levels(birthplace)=="11"] <- "Cayuga.11"
  levels(birthplace)[levels(birthplace)=="1"] <- "Appling.1"
  
  
  new.d <- data.frame(new.d, birthplace)
  new.d <- apply_labels(new.d, birthplace = "Place of birth")
  
  temp.d <- data.frame (new.d.1, birthplace)
  summarytools::view(dfSummary(new.d$birthplace, style = 'grid',
                               max.distinct.values = 100, plain.ascii =   FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace [labelled, factor]	Place of birth	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater Californi 14. Unkown.999	96 ( 15.8% ) 1 ( 0.2% ) 2 ( 0.3% ) 1 ( 0.2% ) 1 ( 0.2% ) 44 ( 7.3% ) 5 ( 0.8% ) 3 ( 0.5% ) 3 ( 0.5% ) 1 ( 0.2% ) 17 ( 2.8% ) 1 ( 0.2% ) 1 ( 0.2% ) 430 ( 71.0% )		1561 (72.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater California).97 14. Unkown.999	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater Californi 14. Unkown.999	1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 164 ( 97.6% )		6 (3.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater California).97 14. Unkown.999	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater Californi 14. Unkown.999	1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 43 ( 95.6% )		129 (74.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater Californi 14. Unkown.999	8 ( 6.5% ) 1 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.8% ) 0 ( 0.0% ) 1 ( 0.8% ) 16 ( 12.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 97 ( 78.2% )		166 (57.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater Californi 14. Unkown.999	85 ( 33.5% ) 0 ( 0.0% ) 2 ( 0.8% ) 1 ( 0.4% ) 1 ( 0.4% ) 44 ( 17.3% ) 4 ( 1.6% ) 2 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 114 ( 44.9% )		833 (76.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. 0 2. 100 3. Cayuga.11 4. 244 5. 25 6. Burke.33 7. 35 8. 37 9. 41 10. 43 11. Ouachita.73 12. 87 13. Sonoma (Greater Californi 14. Unkown.999	1 ( 6.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 13.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 12 ( 80.0% )		1 (6.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

BIRTHPLACE–STATE

• USPS abbreviation for the state, commonwealth, U.S. possession; or CanadaPost abbreviation for the Canadian province/territory in which the patient was born. If the patient has multiple primaries, the state of birth is the same for each tumor. This data item became part of the NAACCR transmission record effective with Volume II, Version 13 in order to include country and state for each geographic item and to use interoperable codes. It supplements the item BIRTHPLACE–COUNTRY [254]. These two data items are intended to replace the item BIRTHPLACE [250].

• Rationale: This is a modification of the current item Birthplace [250] item in order to make use of standard codes, rather than using geographic codes that are only used by cancer registries. The intention is that item 250 be converted to populate the new corresponding, more standard, data items. Codes

• See Appendix B for numeric and alphabetic lists of places and codes (also see Appendix B of the SEER Program Code Manual at seer.cancer.gov/tools/codingmanuals/index.html).

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#252

All data

st_css() #IMPORTANT!

  birthplacestate <- as.factor(trimws(d[,"birthplacestate"]))
  # recode for interpretable birthplace state
  #new.d.n <- data.frame(new.d.n, birthplacestate) # keep NAACCR coding
  levels(birthplacestate)[levels(birthplacestate)=="XX"] <- "Unknown.XX"
  levels(birthplacestate)[levels(birthplacestate)=="YY"] <- "Unknown.YY"
  levels(birthplacestate)[levels(birthplacestate)=="ZZ"] <- "Unknown.ZZ"

  new.d <- data.frame(new.d, birthplacestate)
  new.d <- apply_labels(new.d, birthplacestate = "State of birth")

temp.d <- data.frame (new.d.1, birthplacestate)
summarytools::view(dfSummary(new.d$birthplacestate, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplacestate [labelled, factor]	State of birth	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	3 ( 0.1% ) 17 ( 0.8% ) 4 ( 0.2% ) 1 ( 0.0% ) 77 ( 3.6% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 14 ( 0.6% ) 223 ( 10.3% ) 1 ( 0.0% ) 1 ( 0.0% ) 5 ( 0.2% ) 5 ( 0.2% ) 4 ( 0.2% ) 2 ( 0.1% ) 80 ( 3.7% ) 1 ( 0.0% ) 18 ( 0.8% ) 3 ( 0.1% ) 10 ( 0.5% ) 3 ( 0.1% ) 2 ( 0.1% ) 9 ( 0.4% ) 5 ( 0.2% ) 3 ( 0.1% ) 3 ( 0.1% ) 10 ( 0.5% ) 2 ( 0.1% ) 10 ( 0.5% ) 383 ( 17.7% ) 1 ( 0.0% ) 6 ( 0.3% ) 3 ( 0.1% ) 38 ( 1.8% ) 3 ( 0.1% ) 1213 ( 56.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	1 ( 0.5% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 27 ( 14.3% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.5% ) 2 ( 1.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.5% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 3 ( 1.6% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 5 ( 2.6% ) 12 ( 6.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.6% ) 8 ( 4.2% ) 2 ( 1.1% ) 101 ( 53.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	0 ( 0.0% ) 2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.6% ) 14 ( 8.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 22 ( 12.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 5 ( 2.9% ) 0 ( 0.0% ) 114 ( 65.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	2 ( 0.8% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 33 ( 13.9% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 6 ( 2.5% ) 1 ( 0.4% ) 5 ( 2.1% ) 1 ( 0.4% ) 3 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.8% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 4 ( 1.7% ) 0 ( 0.0% ) 2 ( 0.8% ) 8 ( 3.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 16 ( 6.8% ) 0 ( 0.0% ) 143 ( 60.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 4.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 11 ( 6.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 155 ( 89.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 68 ( 23.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 20 ( 6.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 196 ( 67.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	0 ( 0.0% ) 10 ( 0.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 0.9% ) 221 ( 20.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.2% ) 3 ( 0.3% ) 2 ( 0.2% ) 0 ( 0.0% ) 3 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.2% ) 0 ( 0.0% ) 3 ( 0.3% ) 2 ( 0.2% ) 1 ( 0.1% ) 3 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 5 ( 0.5% ) 0 ( 0.0% ) 2 ( 0.2% ) 309 ( 28.4% ) 0 ( 0.0% ) 4 ( 0.4% ) 0 ( 0.0% ) 8 ( 0.7% ) 1 ( 0.1% ) 491 ( 45.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_state [factor]	1. AK 2. AL 3. AR 4. AZ 5. CA 6. CD 7. CT 8. DE 9. FL 10. GA 11. GU 12. IA 13. IL 14. IN 15. KS 16. KY 17. LA 18. MA 19. MI 20. MO 21. MS 22. NC 23. NJ 24. NY 25. OH 26. OK 27. PA 28. SC 29. TN 30. TX 31. US 32. UT 33. VA 34. WA 35. Unknown.XX 36. Unknown.YY 37. Unknown.ZZ	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 12.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 13 ( 81.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

BIRTHPLACE–COUNTRY

• Code for the country in which the patient was born. If the patient has multiple tumors, all records should contain the same code. This data item became part of the NAACCR transmission record effective with Volume II, Version 13 in order to include country and state for each geographic item and to use interoperable codes. It supplements the item BIRTHPLACE–STATE [252]. These two data items are intended to replace the use of BIRTHPLACE [250].

• Rationale: Place of Birth is helpful for patient matching and can be used when reviewing race and ethnicity. It is an important item in algorithms for imputing race and ethnicity. In addition, adding birthplace data to race and ethnicity allows for a more specific definition of the population being reported. Careful descriptions of ancestry, birthplace, and immigration history of populations studied are needed to make the basis for classification into ethnic groups clear. Birthplace has been associated with variation in genetic, socioeconomic, cultural, and nutritional characteristics that affect patterns of disease. A better understanding of the differences within racial and ethnic categories also can help states develop effective, culturally-sensitive public health prevention programs to decrease the prevalence of high-risk behaviors and increase the use of preventive services.

• See Appendix B for numeric and alphabetic lists of places and codes (also see Appendix B of the SEER Program Code Manual at seer.cancer.gov/tools/codingmanuals/index.html).

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#254

All data

st_css() #IMPORTANT!}

  birthplacecountry <- as.factor(trimws(d[,"birthplacecountry"]))
  #new.d.n <- data.frame(new.d.n, birthplacecountry) # keep NAACCR coding
  # recode for interpretable birthplace country
  levels(birthplacecountry)[levels(birthplacecountry)=="ZZU"] <- "Unknown.ZZU"
  levels(birthplacecountry)[levels(birthplacecountry)=="ZZF"] <- "Africa.ZZF"
  levels(birthplacecountry)[levels(birthplacecountry)=="ZZX"] <- "Non_US.ZZX"
  levels(birthplacecountry)[levels(birthplacecountry)=="ZZE"] <- "Europe NOS.ZZE"
  levels(birthplacecountry)[levels(birthplacecountry)=="ZZC"] <- "Central American NOS.ZZC"
  levels(birthplacecountry)[levels(birthplacecountry)=="ZWE"] <- "Zimbabwe.ZWE"
  levels(birthplacecountry)[levels(birthplacecountry)=="XWF"] <- "West Africa, NOS (French Africa, NOS).XWF"
  levels(birthplacecountry)[levels(birthplacecountry)=="WSM"] <- "Samoa.WSM"
  levels(birthplacecountry)[levels(birthplacecountry)=="VIR"] <- "Virgin Islands (U.S.).VIR"
  levels(birthplacecountry)[levels(birthplacecountry)=="USA"] <- "United States of America (the).USA"
  levels(birthplacecountry)[levels(birthplacecountry)=="UGA"] <- "Uganda.UGA"
  levels(birthplacecountry)[levels(birthplacecountry)=="TTO"] <- "Trinidad and Tobago.TTO"
  levels(birthplacecountry)[levels(birthplacecountry)=="SOM"] <- "Somalia.SOM"
  levels(birthplacecountry)[levels(birthplacecountry)=="SLE"] <- "Sierra Leone.SLE"
  levels(birthplacecountry)[levels(birthplacecountry)=="SEN"] <- "Senegal.SEN"
  levels(birthplacecountry)[levels(birthplacecountry)=="RWA"] <- "Rwanda.RWA"
  levels(birthplacecountry)[levels(birthplacecountry)=="PRT"] <- "Portugal.PRT"
  levels(birthplacecountry)[levels(birthplacecountry)=="PRI"] <- "Puerto Rico.PRI"
  levels(birthplacecountry)[levels(birthplacecountry)=="PAN"] <- "Panama.PAN"
  levels(birthplacecountry)[levels(birthplacecountry)=="NIC"] <- "Nicaragua.NIC"
  levels(birthplacecountry)[levels(birthplacecountry)=="NGA"] <- "Nigeria.NGA"
  levels(birthplacecountry)[levels(birthplacecountry)=="NER"] <- "Niger.NER"
  levels(birthplacecountry)[levels(birthplacecountry)=="MEX"] <- "Mexico.MEX"
  levels(birthplacecountry)[levels(birthplacecountry)=="LCA"] <- "Saint Lucia.LCA"
  levels(birthplacecountry)[levels(birthplacecountry)=="LBR"] <- "Liberia.LBR"
  levels(birthplacecountry)[levels(birthplacecountry)=="JPN"] <- "Japan.JPN"
  levels(birthplacecountry)[levels(birthplacecountry)=="JAM"] <- "Jamaica.JAM"
  levels(birthplacecountry)[levels(birthplacecountry)=="HUN"] <- "Hungary.HUN"
  levels(birthplacecountry)[levels(birthplacecountry)=="HTI"] <- "Haiti.HTI"
  levels(birthplacecountry)[levels(birthplacecountry)=="GUY"] <- "Guyana.GUY"
  levels(birthplacecountry)[levels(birthplacecountry)=="GUM"] <- "Guam.GUM"
  levels(birthplacecountry)[levels(birthplacecountry)=="GRD"] <- "Grenada.GRD"
  levels(birthplacecountry)[levels(birthplacecountry)=="GMB"] <- "Gambia (the).GMB"
  levels(birthplacecountry)[levels(birthplacecountry)=="GHA"] <- "Ghana.GHA"
  levels(birthplacecountry)[levels(birthplacecountry)=="GEO"] <- "Georgia.GEO"
  levels(birthplacecountry)[levels(birthplacecountry)=="GBR"] <- "United Kingdom of Great Britain and Northern Ireland (the).GBR"
  levels(birthplacecountry)[levels(birthplacecountry)=="FRA"] <- "France.FRA"
  levels(birthplacecountry)[levels(birthplacecountry)=="ETH"] <- "Ethiopia.ETH"
  levels(birthplacecountry)[levels(birthplacecountry)=="ERI"] <- "Eritrea.ERI"
  levels(birthplacecountry)[levels(birthplacecountry)=="ENG"] <- "England.ENG"
  levels(birthplacecountry)[levels(birthplacecountry)=="DOM"] <- "Dominican Republic (the).DOM"
  levels(birthplacecountry)[levels(birthplacecountry)=="DEU"] <- "Germany.DEU"
  levels(birthplacecountry)[levels(birthplacecountry)=="CUB"] <- "Cuba.CUB"
  levels(birthplacecountry)[levels(birthplacecountry)=="CRI"] <- "Costa Rica.CRI"
  levels(birthplacecountry)[levels(birthplacecountry)=="COG"] <- "Congo (the).COG"
  levels(birthplacecountry)[levels(birthplacecountry)=="CMR"] <- "Cameroon.CMR"
  levels(birthplacecountry)[levels(birthplacecountry)=="CIV"] <- "Cote d'Ivoire.CIV"
  levels(birthplacecountry)[levels(birthplacecountry)=="CAN"] <- "Canada.CAN"
  levels(birthplacecountry)[levels(birthplacecountry)=="BRB"] <- "Barbados.BRB"
  levels(birthplacecountry)[levels(birthplacecountry)=="BLZ"] <- "Belize.BLZ"
  levels(birthplacecountry)[levels(birthplacecountry)=="BHS"] <- "Bahamas (the).BHS"
  levels(birthplacecountry)[levels(birthplacecountry)=="ARE"] <- "United Arab Emirates (the).ARE"

  
  new.d <- data.frame(new.d, birthplacecountry)
  new.d <- apply_labels(new.d, birthplacecountry = "Country of birth")
  
temp.d <- data.frame (new.d.1, birthplacecountry)
summarytools::view(dfSummary(new.d$birthplacecountry, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplacecountry [labelled, factor]	Country of birth	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 9 ( 0.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 10 ( 0.5% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 911 ( 42.0% ) 1 ( 0.0% ) 1214 ( 56.0% ) 1 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 77 ( 40.7% ) 1 ( 0.5% ) 102 ( 54.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 54 ( 31.0% ) 0 ( 0.0% ) 114 ( 65.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 3.8% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 78 ( 32.9% ) 0 ( 0.0% ) 143 ( 60.3% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 19 ( 10.9% ) 0 ( 0.0% ) 155 ( 89.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 93 ( 32.1% ) 0 ( 0.0% ) 196 ( 67.6% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 0.3% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 587 ( 54.0% ) 0 ( 0.0% ) 491 ( 45.2% ) 1 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	birthplace_country [factor]	1. Bahamas (the).BHS 2. Belize.BLZ 3. Canada.CAN 4. Cameroon.CMR 5. Cuba.CUB 6. England.ENG 7. Ethiopia.ETH 8. France.FRA 9. Georgia.GEO 10. Ghana.GHA 11. Gambia (the).GMB 12. Guam.GUM 13. Haiti.HTI 14. Jamaica.JAM 15. KEN 16. Niger.NER 17. Nigeria.NGA 18. Nicaragua.NIC 19. Panama.PAN 20. Senegal.SEN 21. Trinidad and Tobago.TTO 22. United States of America 23. Africa.ZZF 24. Unknown.ZZU 25. Non_US.ZZX	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 18.8% ) 0 ( 0.0% ) 13 ( 81.2% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CENSUS BLOCK GROUP 2000

• Description: This field is provided for coding the block group of patient’s residence at time of diagnosis, as defined by the 2000 Census.
• Rationale: A block group is a subdivision of a census tract designed to have an average of 1500 people, versus a census tract’s average of 4500 people. All land area in the United States is described by a census block group in the 2000 Census. The Census Bureau publishes detailed population and socioeconomic data at this level.
• Block groups thus offer a high level of specificity for geographical and socioeconomic analyses. A block group has no meaning in the absence of a census tract. Refer to Census Tr Certainty 2000 [365] to ascertain basis of assignment of Census Block Group 2000.
• Comment: Numerous registries find the distinction between “attempted, could not be determined” (zero) and “not coded” (blank) to be useful for geocoding planning purposes.
• Note: The values 1 through 9 are nominal, with no hierarchy of values. This number determines the first digit of all the blocks which comprise the block group; for instance, census block group 3 would contain blocks numbered 3000 to 3999.
• Codes
  • 0 Census block group assignment was attempted, but the value could not be determined
  • 1-9 Census block group values as defined by the Census Bureau
  • Blank Census Block Group 2000 not coded
• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#362

All data

st_css() #IMPORTANT!

  censusblockgroup2000 <- as.factor(trimws(d[,"censusblockgroup2000"]))

  new.d <- data.frame(new.d, censusblockgroup2000)
  new.d <- apply_labels(new.d, censusblockgroup2000 = "census_block_group_2000")

temp.d <- data.frame (new.d.1, censusblockgroup2000)
summarytools::view(dfSummary(new.d$censusblockgroup2000, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	censusblockgroup2000 [labelled, factor]	census_block_group_2000	1. 1	1 ( 100.0% )		2166 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2000 [factor]	1. 1	1 ( 100.0% )		15 (93.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CENSUS BLOCK GROUP 2010

• Description: This field is provided for coding the block group of patient’s residence at time of diagnosis, as defined by the 2010 Census.

• Rationale: A block group is a subdivision of a census tract designed to have an average of 1500 people, versus a census tract’s average of 4500 people. All land area in the United States is described by a census block group in the 2010 Census. The Census Bureau publishes detailed population and socioeconomic data at this level. Block groups thus offer a high level of specificity for geographical and socioeconomic analyses.

• A block group has no meaning in the absence of a census tract. Refer to Census Tr Certainty 2010 [367] to ascertain basis of assignment of Census Block Group 2010.

• Comment: Numerous registries find the distinction between “attempted, could not be determined” (zero) and “not coded” (blank) to be useful for geocoding planning purposes.

• Note: The values 1 through 9 are nominal, with no hierarchy of values. This number determines the first digit of all the blocks which comprise the block group; for instance, census block group 3 would contain blocks numbered 3000 to 3999.

• Codes

  • 0 Census block group assignment was attempted, but the value could not be determined
  • 1-9 Census block group values as defined by the Census Bureau
  • Blank Census Block Group 2010 not coded

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#363

All data

st_css() #IMPORTANT!

  censusblockgroup2010 <- as.factor(trimws(d[,"censusblockgroup2010"]))

  new.d <- data.frame(new.d, censusblockgroup2010)
  new.d <- apply_labels(new.d, censusblockgroup2010 = "census_block_group_2010")

temp.d <- data.frame (new.d.1, censusblockgroup2010)
summarytools::view(dfSummary(new.d$censusblockgroup2010, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	censusblockgroup2010 [labelled, factor]	census_block_group_2010	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	672 ( 34.8% ) 527 ( 27.3% ) 364 ( 18.9% ) 240 ( 12.4% ) 62 ( 3.2% ) 7 ( 0.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 55 ( 2.9% )		238 (11.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	61 ( 32.4% ) 63 ( 33.5% ) 40 ( 21.3% ) 17 ( 9.0% ) 4 ( 2.1% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% )		1 (0.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	67 ( 38.5% ) 52 ( 29.9% ) 37 ( 21.3% ) 17 ( 9.8% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	56 ( 32.2% ) 56 ( 32.2% ) 37 ( 21.3% ) 17 ( 9.8% ) 8 ( 4.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	91 ( 31.4% ) 0 ( 0.0% ) 10 ( 3.4% ) 111 ( 38.3% ) 22 ( 7.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 55 ( 19.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	390 ( 35.9% ) 351 ( 32.3% ) 237 ( 21.8% ) 78 ( 7.2% ) 27 ( 2.5% ) 4 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_block_group_2010 [factor]	1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 7. 7 8. 8 9. 9	7 ( 43.8% ) 5 ( 31.2% ) 3 ( 18.8% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CENSUS TR CERTAINTY 2000

• Description: Code indicating basis of assignment of census tract for an individual record. Helpful in identifying cases tracted from incomplete information or P.O. Box. This item is not coded by the hospital. Central registry staff assign the code.
• Codes
  • 1 Census tract based on complete and valid street address of residence
  • 2 Census tract based on residence ZIP + 4
  • 3 Census tract based on residence ZIP + 2
  • 4 Census tract based on residence ZIP code only
  • 5 Census tract based on ZIP code of P.O. Box
  • 6 Census tract/BNA based on residence city where city has only one census tract, or based on residence ZIP code where ZIP code has only one census tract
  • 9 Not assigned, geocoding attempted
  • Blank Not assigned, geocoding not attempted
• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#365

All data

st_css() #IMPORTANT!

  censustrcertainty2000 <- as.factor(trimws(d[,"censustrcertainty2000"]))
  levels(censustrcertainty2000)[levels(censustrcertainty2000)=="1"] <- "complete_and_valid.1"
  levels(censustrcertainty2000)[levels(censustrcertainty2000)=="9"] <- "Not_assigned.9"

  new.d <- data.frame(new.d, censustrcertainty2000)
  new.d <- apply_labels(new.d, censustrcertainty2000 = "census_tr_certainty_2000")

temp.d <- data.frame (new.d.1, censustrcertainty2000)
summarytools::view(dfSummary(new.d$censustrcertainty2000, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	censustrcertainty2000 [labelled, factor]	census_tr_certainty_2000	1. complete_and_valid.1 2. Not_assigned.9	9 ( 1.5% ) 599 ( 98.5% )		1559 (71.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	0 ( 0.0% ) 189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	0 ( 0.0% ) 174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	1 ( 0.4% ) 236 ( 99.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	1 ( 100.0% ) 0 ( 0.0% )		173 (99.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2000 [factor]	1. complete_and_valid.1 2. Not_assigned.9	7 ( 100.0% ) 0 ( 0.0% )		9 (56.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CENSUS TR CERTAINTY 2000

• Description: Code indicating basis of assignment of census tract for an individual record. Helpful in identifying cases tracted from incomplete information or P.O. Box. This item is not coded by the hospital. Central registry staff assign the code.

• Codes

  • 1 Census tract based on complete and valid street address of residence
  • 2 Census tract based on residence ZIP + 4
  • 3 Census tract based on residence ZIP + 2
  • 4 Census tract based on residence ZIP code only
  • 5 Census tract based on ZIP code of P.O. Box
  • 6 Census tract/BNA based on residence city where city has only one census tract, or based on residence ZIP code where ZIP code has only one census tract
  • 9 Not assigned, geocoding attempted
  • Blank Not assigned, geocoding not attempted

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#367

All data

st_css() #IMPORTANT!

  censustrcertainty2010 <- as.factor(trimws(d[,"censustrcertainty2010"]))
  levels(censustrcertainty2010)[levels(censustrcertainty2010)=="1"] <- "complete_and_valid.1"
  levels(censustrcertainty2010)[levels(censustrcertainty2010)=="2"] <- "ZIP_4.2"
  levels(censustrcertainty2010)[levels(censustrcertainty2010)=="4"] <- "ZIP_code_only.4"
  levels(censustrcertainty2010)[levels(censustrcertainty2010)=="5"] <- "ZIP_code_of_PO_Box.5"
  levels(censustrcertainty2010)[levels(censustrcertainty2010)=="9"] <- "Not_assigned.9"

  new.d <- data.frame(new.d, censustrcertainty2010)
  new.d <- apply_labels(new.d, censustrcertainty2010 = "census_tr_certainty_2010")

temp.d <- data.frame (new.d.1, censustrcertainty2010)
summarytools::view(dfSummary(new.d$censustrcertainty2010, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	censustrcertainty2010 [labelled, factor]	census_tr_certainty_2010	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	2136 ( 98.6% ) 3 ( 0.1% ) 2 ( 0.1% ) 24 ( 1.1% ) 2 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	182 ( 96.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 3.2% ) 1 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	167 ( 96.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 4.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	228 ( 96.2% ) 2 ( 0.8% ) 0 ( 0.0% ) 6 ( 2.5% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	173 ( 99.4% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	288 ( 99.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	1082 ( 99.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	census_tr_certainty_2010 [factor]	1. complete_and_valid.1 2. ZIP_4.2 3. ZIP_code_only.4 4. ZIP_code_of_PO_Box.5 5. Not_assigned.9	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SEQUENCE NUMBER–CENTRAL

• Description: Code indicates the sequence of all reportable neoplasms over the lifetime of the person. This data item differs from Sequence Number-Hospital [560], because the definitions of reportable neoplasms often vary between a hospital and a central registry. Each neoplasm is assigned a different number. Sequence Number 00 indicates that the person has had only one in situ or one malignant neoplasm as defined by the Federal reportable list (regardless of central registry reference date). Sequence Number 01 indicates the first of two or more reportable neoplasms, but 02 indicates the second of two or more reportable neoplasms, and so on. Because the time period of Sequence Number is a person’s lifetime, reportable neoplasms not included in the central registry (those that occur outside the registry catchment area or before the reference date) also are allotted a sequence number. For example, a registry may contain a single record for a patient with a sequence number of 02 because the first reportable neoplasm preceded the central registry’s reference date.

• Reporting Requirements: Federally Required and State/Province Defined: The Federal or SEER/NPCR standard defining the reportable neoplasms is described in Chapter III, Standards For Tumor Inclusion and Reportability. It is assumed that this shared standard is the “minimum” definition of reportability. Individual central cancer registries may define additional neoplasms as reportable.

• Numeric codes in the 00-59 range indicate the sequence of neoplasms of in situ or malignant behavior (2 or 3) at the time of diagnosis, which SEER/NPCR standards require to be reported. Codes 60 to 87 indicate the sequence of non-malignant tumors (as defined in Chapter III) and any other neoplasms that the central registry has defined as reportable. Neoplasms required by SEER/NPCR with an in situ or malignant behavior at the time of diagnosis are sequenced completely independently of this higher-numbered category. Sequence Number-Hospital does not affect Sequence Number-Central. The two notational systems are independent but central registries should take Sequence Number-Hospital [560] into account when coding Sequence Number Central.

• Rationale: The purpose of sequencing based on the patient’s lifetime is to truly identify the 00s, the people who only had one malignant primary in their lifetimes for survival analysis. If a central registry sequences by just what is reported to them, then it will be unclear whether 00 means the person only had one malignant primary in his lifetime or the person had one malignant primary since the central registry started collecting data. The Federally required reportable list has changed throughout the years, so the registry must use the appropriate reportable list for the year of diagnosis. The central registry reference date will not affect Sequence Number-Central.

• Codes

  • 00 One primary in the patient’s lifetime
  • 01 First of two or more primaries
  • 02 Second of two or more primaries
  • 03 Third of two or more primaries
  • 04 Forth of two or more primaries

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#380

All data

st_css() #IMPORTANT!

  sequencenumbercentral <- as.factor(trimws(d[,"sequencenumbercentral"]))
  levels(sequencenumbercentral)[levels(sequencenumbercentral)=="0"] <- "One_primary.0"
  levels(sequencenumbercentral)[levels(sequencenumbercentral)=="1"] <- "First_of_two_or_more.1"
  levels(sequencenumbercentral)[levels(sequencenumbercentral)=="2"] <- "Second_of_two_or_more.2"
  levels(sequencenumbercentral)[levels(sequencenumbercentral)=="3"] <- "Third_of_two_or_more.2"
  levels(sequencenumbercentral)[levels(sequencenumbercentral)=="4"] <- "Forth_of_two_or_more.4"

  new.d <- data.frame(new.d, sequencenumbercentral)
  new.d <- apply_labels(new.d, sequencenumbercentral = "sequence_number_central")

temp.d <- data.frame (new.d.1, sequencenumbercentral)
summarytools::view(dfSummary(new.d$sequencenumbercentral, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequencenumbercentral [labelled, factor]	sequence_number_central	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	1997 ( 92.2% ) 49 ( 2.3% ) 105 ( 4.8% ) 14 ( 0.6% ) 2 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	178 ( 94.2% ) 4 ( 2.1% ) 5 ( 2.6% ) 2 ( 1.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	161 ( 92.5% ) 5 ( 2.9% ) 6 ( 3.4% ) 2 ( 1.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	224 ( 94.5% ) 2 ( 0.8% ) 11 ( 4.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	152 ( 87.4% ) 4 ( 2.3% ) 13 ( 7.5% ) 4 ( 2.3% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	273 ( 94.1% ) 3 ( 1.0% ) 12 ( 4.1% ) 2 ( 0.7% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	994 ( 91.4% ) 30 ( 2.8% ) 58 ( 5.3% ) 4 ( 0.4% ) 1 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	sequence_number_central [factor]	1. One_primary.0 2. First_of_two_or_more.1 3. Second_of_two_or_more.2 4. Third_of_two_or_more.2 5. Forth_of_two_or_more.4	15 ( 93.8% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DATE OF DIAGNOSIS

• Date of initial diagnosis by a recognized medical practitioner for the tumor being reported whether clinically or microscopically confirmed. See Chapter X for date format.

• For more discussion on determining date of diagnosis, consult the SEER Program Coding and Staging Manual or CoC STORE manual.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=21#390

All data

  dateofdiagnosis <- trimws(d[,"dateofdiagnosis"])
  #new.d.n <- data.frame(new.d.n, dateofdiagnosis) # keep NAACCR coding
  
  select99 <- substr(dateofdiagnosis, start=7, stop=8)=="99"
  dateofdiagnosis[select99] <- substr(dateofdiagnosis[select99], start=1, stop=6)
  select6 <- nchar(trimws(dateofdiagnosis))==6
  dateofdiagnosis[select6] <- as.Date(as.yearmon(dateofdiagnosis[select6], c("%Y%m")))
  select8 <- nchar(trimws(dateofdiagnosis))==8
  dateofdiagnosis[select8] <- as.Date(dateofdiagnosis[select8], c("%Y%m%d"))
  select4 <- nchar(trimws(dateofdiagnosis))==4
  dateofdiagnosis[select4] <- as.Date(dateofdiagnosis[select4], c("%Y"))


  
  dateofdiagnosis <- as.Date(as.numeric(dateofdiagnosis), origin = "1970-01-01")
  new.d <- data.frame(new.d, dateofdiagnosis)
  new.d <- apply_labels(new.d, dateofdiagnosis = "Date of Diagnosis")

  temp.d <- data.frame (new.d.1, dateofdiagnosis)
summarytools::view(dfSummary(new.d$dateofdiagnosis, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	dateofdiagnosis [labelled, Date]	Date of Diagnosis	min : 2011-08-01 med : 2016-01-26 max : 2018-12-01 range : 7y 4m 0d	533 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	1. 2015-01-01 2. 2015-02-01 3. 2015-03-01 4. 2015-04-01 5. 2015-05-01 6. 2015-06-01 7. 2015-07-01 8. 2015-08-01 9. 2015-09-01 10. 2015-10-01 11. 2015-11-01 12. 2015-12-01 13. 2016-01-01 14. 2016-02-01 15. 2016-03-01 16. 2016-04-01 17. 2016-05-01 18. 2016-06-01 19. 2016-07-01 20. 2016-08-01 21. 2016-09-01 22. 2016-10-01 23. 2016-11-01 24. 2016-12-01 25. 2017-02-01 26. 2017-03-01 27. 2017-06-01 28. 2017-08-01 29. 2017-11-01 30. 2017-12-01	8 ( 4.2% ) 4 ( 2.1% ) 9 ( 4.8% ) 9 ( 4.8% ) 4 ( 2.1% ) 7 ( 3.7% ) 10 ( 5.3% ) 12 ( 6.3% ) 6 ( 3.2% ) 3 ( 1.6% ) 9 ( 4.8% ) 9 ( 4.8% ) 6 ( 3.2% ) 5 ( 2.6% ) 13 ( 6.9% ) 15 ( 7.9% ) 9 ( 4.8% ) 8 ( 4.2% ) 5 ( 2.6% ) 10 ( 5.3% ) 5 ( 2.6% ) 2 ( 1.1% ) 6 ( 3.2% ) 4 ( 2.1% ) 1 ( 0.5% ) 2 ( 1.1% ) 2 ( 1.1% ) 2 ( 1.1% ) 3 ( 1.6% ) 1 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	min : 2015-01-05 med : 2016-01-22 max : 2017-09-11 range : 2y 8m 6d	146 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	min : 2015-01-01 med : 2015-11-01 max : 2016-12-01 range : 1y 11m 0d	24 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	min : 2015-01-01 med : 2016-08-01 max : 2018-12-01 range : 3y 11m 0d	48 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	min : 2015-01-01 med : 2016-03-22 max : 2016-12-30 range : 1y 11m 29d	216 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	min : 2015-01-01 med : 2016-01-19 max : 2018-09-26 range : 3y 8m 25d	458 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_diagnosis [Date]	min : 2011-08-01 med : 2013-05-01 max : 2015-04-01 range : 3y 8m 0d	15 distinct values		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

PRIMARY SITE

• Code for the primary site of the tumor being reported using either ICD-O-2 or ICD-O-3. NAACCR adopted ICD-O-2 as the standard coding system for tumors diagnosed beginning January 1, 1992. In addition, NAACCR recommended that tumors diagnosed prior to 1992 be converted to ICD-O-2. The topography (primary site) codes did not change between ICD-O-2 and ICD-O-3.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#400

  primarysite <- as.factor(d[,"primarysite"])
  levels(primarysite) <- list(Prostate="C619") # other codings become NA
  new.d <- data.frame(new.d, primarysite)
  new.d <- apply_labels(new.d, primarysite = "Primary Tumor Site")
  
  #cro(new.d$primarysite)# this is pretty but doesn't show NAs
  primarysite<-count(new.d$primarysite)
  colnames(primarysite)<- c("Primary site", "Total")
  kable(primarysite, format = "simple", align = 'l', caption = "Overview of 8 Registries")

Overview of 8 Registries

Primary site	Total
Prostate	2166
NA	1

GRADE

• Code for the grade or degree of differentiation of the reportable tumor. For lymphomas and leukemias, field also is used to indicate T-, B-, Null-, or NK-cell origin.

• See the grade tables on page 67 of ICD-O-3.16 See also the most recent CoC STORE manual and SEER Program Code Manual, for site specific coding rules and conversions.

  • Grade I
    
  • Grade II
    
  • Grade III
    
  • Grade IV
    
  • T-cell
    
  • B-cell
    
  • Null cell
    
  • NK (natural killer) cell
    
  • Grade/differentiation unknown, not stated, or not applicable

• Comment: Use the most recent Hematopoietic and Lymphoid rules for assigning grades 5-8.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#440
  
  

All data

  grade <- as.factor(d[,"grade"])
  levels(grade) <- list(Grade_I.1="1",
                        Grade_II.2="2",
                        Grade_III.3="3",
                        Grade_IV.4="4",
                        T_cell.5="5",
                        B_cell.6="6",
                        Null_cell.7="7",
                        NK_cell.8="8",
                        Unknown.9="9")
  new.d <- data.frame(new.d, grade)
  new.d <- apply_labels(new.d, grade = "Tumor Grade")
  
  #cro(new.d$grade)# this is pretty but doesn't show NAs
  #summary(new.d$grade)
temp.d <- data.frame (new.d.1, grade)
summarytools::view(dfSummary(new.d$grade, style = 'grid', max.distinct.values = 10, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [labelled, factor]	Tumor Grade	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	375 ( 17.6% ) 1156 ( 54.2% ) 589 ( 27.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 13 ( 0.6% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	40 ( 21.2% ) 108 ( 57.1% ) 39 ( 20.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	57 ( 32.8% ) 93 ( 53.4% ) 23 ( 13.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	47 ( 19.8% ) 120 ( 50.6% ) 68 ( 28.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	17 ( 12.0% ) 83 ( 58.5% ) 41 ( 28.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	27 ( 9.3% ) 153 ( 52.8% ) 110 ( 37.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	185 ( 17.1% ) 592 ( 54.6% ) 301 ( 27.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 0.6% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade [factor]	1. Grade_I.1 2. Grade_II.2 3. Grade_III.3 4. Grade_IV.4 5. T_cell.5 6. B_cell.6 7. Null_cell.7 8. NK_cell.8 9. Unknown.9	2 ( 12.5% ) 7 ( 43.8% ) 7 ( 43.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DIAGNOSTIC CONFIRMATION

• Description: Code for the best method of diagnostic confirmation of the cancer being reported at any time in the patient’s history.
• Rationale: Diagnostic confirmation is useful to calculate rates based on microscopically confirmed cancers. Full incidence calculations must also include tumors that are only confirmed clinically. The percentage of tumors that not micropscopically confirmed is an indication of whether case finding is including sources outside of pathology reports.
• Codes
  • 1 Positive histology
  • 2 Positive cytology
  • 3 Positive histology PLUS - positive immunophenotyping AND/OR positive genetic studies (Used only for hematopoietic and lymphoid neoplasms M-9590/3-9992/3)
  • 4 Positive microscopic confirmation, method not specified
  • 5 Positive laboratory test/marker study
  • 6 Direct visualization without microscopic confirmation
  • 7 Radiography and/or other imaging techniques without microscopic confirmation
  • 8 Clinical diagnosis only (other than 5, 6, or 7)
  • 9 Unknown whether or not microscopically confirmed; death certificate only
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#490
  
  

All data

st_css() #IMPORTANT!

  diagnosticconfirmation <- as.factor(trimws(d[,"diagnosticconfirmation"]))
  levels(diagnosticconfirmation)[levels(diagnosticconfirmation)=="1"] <- "Positive_histology.1"

  new.d <- data.frame(new.d, diagnosticconfirmation)
  new.d <- apply_labels(new.d, diagnosticconfirmation = "diagnostic_confirmation")

temp.d <- data.frame (new.d.1, diagnosticconfirmation)
summarytools::view(dfSummary(new.d$diagnosticconfirmation, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnosticconfirmation [labelled, factor]	diagnostic_confirmation	1. Positive_histology.1	2167 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	1087 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	diagnostic_confirmation [factor]	1. Positive_histology.1	16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TYPE OF REPORTING SOURCE

- This variable codes the source documents used to abstract the majority of information on the tumor being reported. This may not be the source of original case finding (for example, if a case is identified through a pathology laboratory report review and all source documents used to abstract the case are from the physician’s office, code this item 4).

• Rationale: The code in this field can be used to explain why information may be incomplete on a tumor. For example, death certificate only cases have unknown values for many data items, so one may want to exclude them from some analyses. The field also is used to monitor the success of non-hospital case reporting and follow-back mechanisms. All population-based registries should have some death certificate-only cases where no hospital admission was involved, but too high a percentage can imply both shortcomings in case-finding and that follow-back to uncover missed hospital reports was not complete.

• Coding Instructions: Code in the following priority order: 1, 2, 8, 4, 3, 5, 6, 7. This is a change to reflect the addition of codes 2 and 8 and to prioritize laboratory reports over nursing home reports. The source facilities included in the previous code 1 (hospital inpatient and outpatient) are split between codes 1, 2, and 8.

• This data item is intended to indicate the completeness of information available to the abstractor. Reports from health plans (e.g., Kaiser, Veterans Administration, military facilities) in which all diagnostic and treatment information is maintained centrally and is available to the abstractor are expected to be at least as complete as reports for hospital inpatients, which is why these sources are grouped with inpatients and given the code with the highest priority.

• Sources coded with ‘2’ usually have complete information on the cancer diagnosis, staging, and treatment.

• Sources coded with ‘8’ would include, but would not be limited to, outpatient surgery and nuclear medicine services. A physician’s office that calls itself a surgery center should be coded as a physician’s office. Surgery centers are equipped and staffed to perform surgical procedures under general anesthesia. If a physician’s office calls itself a surgery center, but cannot perform surgical procedures under general anesthesia, code as a physician office.

• Codes

  • 1 Hospital inpatient; Managed health plans with comprehensive, unified medical records
  • 2 Radiation Treatment Centers or Medical Oncology Centers (hospital-affiliated or independent)
  • 3 Laboratory only (hospital-affiliated or independent)
  • 4 Physician’s office/private medical practitioner (LMD)
  • 5 Nursing/convalescent home/hospice
  • 6 Autopsy only
  • 7 Death certificate only
  • 8 Other hospital outpatient units/surgery centers

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#500

All data

  typeofreportingsource <- as.factor(d[,"typeofreportingsource"])
  levels(typeofreportingsource) <- list(Hospital.1="1",
                                 Radiation_Tx.2="2",
                                 Laboratory_Only.3="3",
                                 Physician.4="4",
                                 Nursing.5="5",
                                 Autopsy.6="6",
                                 Death_Certificate.7="7",
                                 Other_Hospital.Unit.8="8")
  new.d <- data.frame(new.d, typeofreportingsource)
  new.d <- apply_labels(new.d, typeofreportingsource = "Source of Tumor Information")
  
  #summary(new.d$typeofreportingsource)

temp.d <- data.frame (new.d.1, typeofreportingsource)
summarytools::view(dfSummary(new.d$typeofreportingsource, style = 'grid', max.distinct.values = 10, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	typeofreportingsource [labelled, factor]	Source of Tumor Information	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	1992 ( 91.9% ) 66 ( 3.0% ) 53 ( 2.4% ) 30 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 26 ( 1.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	186 ( 98.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	169 ( 97.1% ) 3 ( 1.7% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	228 ( 96.2% ) 6 ( 2.5% ) 0 ( 0.0% ) 2 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	169 ( 97.1% ) 0 ( 0.0% ) 4 ( 2.3% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	255 ( 87.9% ) 8 ( 2.8% ) 11 ( 3.8% ) 16 ( 5.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	970 ( 89.2% ) 49 ( 4.5% ) 38 ( 3.5% ) 5 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 25 ( 2.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	type_of_reporting_source [factor]	1. Hospital.1 2. Radiation_Tx.2 3. Laboratory_Only.3 4. Physician.4 5. Nursing.5 6. Autopsy.6 7. Death_Certificate.7 8. Other_Hospital.Unit.8	15 ( 93.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

HISTOLOGIC TYPE ICD-O-3

• Description: Codes for the histologic type of the tumor being reported using ICD-O-3. NAACCR adopted ICD-O-3 as the standard coding system for tumors diagnosed in 2001 and later, and recommended that prior tumors be converted from ICD-O-2. Effective with 2010 diagnoses, this item also includes histology codes as per the 2008 WHO Hematopoietic/Lymphoid publication39, which are listed on pages 3-5 of the NAACCR 2010 Implementation Guidelines. http://www.naaccr.org/StandardsandRegistryOperations/ImplementationGuidelines.aspx.

• Note: See Histology (92-00) ICD-O-2 [420] for ICD-O-2 codes. Effective with 2010 diagnoses, this item also includes histology codes as per the 2008 WHO Hematopoietic/Lymphoid publication 39, which are listed on pages 3-5 of the NAACCR 2010 Implementation Guidelines. http://www.naaccr.org/LinkClick.aspx?fileticket=U-3o31G2Lik%3d&tabid=126&mid=466

• Codes

  • See ICD-O-3,14 Morphology Section and the SEER Hematopoietic database.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#522

All data

st_css() #IMPORTANT!

  histologictypeicdo3 <- as.factor(trimws(d[,"histologictypeicdo3"]))
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8000"] <- "Neoplasm_malignant.8000"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8010"] <- "Carcinoma_NOS.8010"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8140"] <- "Adenocarcinoma_NOS.8140"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8323"] <- "Mixed_cell_adenocarcinoma.8323"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8480"] <- "Mucinous_adenocarcinoma.8480 "
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8481"] <- "Mucin_producing_adenocarcinoma.8481"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8490"] <- "Signet_ring_cell_adenocarcinoma.8490"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8500"] <- "Invasive_breast_carcinoma.8500"
  levels(histologictypeicdo3)[levels(histologictypeicdo3)=="8550"] <- "Acinar_cell_tumor.8550"

  new.d <- data.frame(new.d, histologictypeicdo3)
  new.d <- apply_labels(new.d, histologictypeicdo3 = "histologic_type_icdo3")

temp.d <- data.frame (new.d.1, histologictypeicdo3)
summarytools::view(dfSummary(new.d$histologictypeicdo3, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologictypeicdo3 [labelled, factor]	histologic_type_icdo3	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	5 ( 0.2% ) 5 ( 0.2% ) 2138 ( 98.7% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 3 ( 0.1% ) 3 ( 0.1% ) 10 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	0 ( 0.0% ) 0 ( 0.0% ) 186 ( 98.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	0 ( 0.0% ) 0 ( 0.0% ) 174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	1 ( 0.4% ) 0 ( 0.0% ) 235 ( 99.2% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	0 ( 0.0% ) 1 ( 0.6% ) 171 ( 98.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	0 ( 0.0% ) 0 ( 0.0% ) 285 ( 98.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 4 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	4 ( 0.4% ) 4 ( 0.4% ) 1071 ( 98.5% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 6 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	histologic_type_icdo3 [factor]	1. Neoplasm_malignant.8000 2. Carcinoma_NOS.8010 3. Adenocarcinoma_NOS.8140 4. Mixed_cell_adenocarcinoma 5. Mucinous_adenocarcinoma.8 6. Mucin_producing_adenocarc 7. Signet_ring_cell_adenocar 8. Invasive_breast_carcinoma 9. Acinar_cell_tumor.8550	0 ( 0.0% ) 0 ( 0.0% ) 16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

BEHAVIOR CODE ICD-O-3

• Description: Code for the behavior of the tumor being reported using ICD-O-3. NAACCR adopted ICD-O-3 as the standard coding system for tumors diagnosed beginning January 1, 2001, and later recommended that prior cases be converted from ICD-O-2. See Behavior (92-00) ICD-O-2 [430], for ICD-O-2 codes.

• Juvenile astrocytoma is coded as borderline in ICD-O-3; North American registries report as 9421/3. Clarification of Required Status Behavior is required by all standard-setting organizations for tumors diagnosed on or after January 1, 2001, and recommended (by conversion from ICD-O-2 codes) for tumors diagnosed before 2001.

• When the histologic type is coded according to the ICD-O-3, the histology code must be reported in Histologic Type ICD-O-3 [522], with behavior coded in Behavior Code ICD-O-3 [523].

• For information on required status for related data items for histologic type and behavior when coded according to ICD-O-2, see Histology (92-00) ICD-O-2 [420] and Behavior (92-00) ICD-O-2 [430].

• Codes

  • Valid codes are 0-3. See ICD-O-3,14 page 66, for behavior codes and definitions.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#523

All data

st_css() #IMPORTANT!

  behaviorcodeicdo3 <- as.factor(trimws(d[,"behaviorcodeicdo3"]))

  new.d <- data.frame(new.d, behaviorcodeicdo3)
  new.d <- apply_labels(new.d, behaviorcodeicdo3 = "behavior_code_icdo3")

temp.d <- data.frame (new.d.1, behaviorcodeicdo3)
summarytools::view(dfSummary(new.d$behaviorcodeicdo3, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	behaviorcodeicdo3 [labelled, factor]	behavior_code_icdo3	1. 3	2167 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

PRIMARY PAYER AT DX

• Description: Primary payer/insurance carrier at the time of initial diagnosis and/or treatment at the reporting facility.

• Rationale: This item is used in financial analysis and as an indicator for quality and outcome analyses.

-Codes
+ 01 Not insured
+ 02 Not insured, self-pay
+ 10 Insurance, NOS
+ 20 Private Insurance: Managed care, HMO, or PPO
+ 21 Private Insurance: Fee-for-Service
+ 31 Medicaid
+ 35 Medicaid - Administered through a Managed Care plan
+ 60 Medicare/Medicare, NOS
+ 61 Medicare with supplement, NOS
+ 62 Medicare - Administered through a Managed Care plan
+ 63 Medicare with private supplement
+ 64 Medicare with Medicaid eligibility
+ 65 TRICARE
+ 66 Military
+ 67 Veterans Affairs
+ 68 Indian/Public Health Service
+ 99 Insurance status unknown

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#630

All data

  primarypayeratdx <- as.factor(d[,"primarypayeratdx"])
  levels(primarypayeratdx) <- list(Not_insured.1="1",
                               Not_insured_self_pay.2="2",
                               Insurance.10="10",
                               Private_managed.20="20",
                               Private_FFS.21="21", # fee-for-service
                               Medicaid.31="31",
                               Medicaid_managed_care.35="35",
                               Medicare_medicare.60="60",
                               Medicare_suppl.61="61",
                               Medicare_managed_care.62="62",
                               Medicare_private_suppl.63="63",
                               Medicare_medicaid.64="64",
                               TRICARE.65="65",
                               Military.66="66",
                               Veterans_Affairs.67="67",
                               Indian_PHS.68="68",
                               Unknown.99="99")
    primarypayeratdx <- relevel(primarypayeratdx, ref="Private_managed.20")
    new.d <- data.frame(new.d, primarypayeratdx)
    new.d <- apply_labels(new.d, primarypayeratdx = "Primary payer/insurance at the time of diagnosis")
    #summary(new.d$primarypayeratdx)
temp.d <- data.frame (new.d.1, primarypayeratdx)
summarytools::view(dfSummary(new.d$primarypayeratdx, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primarypayeratdx [labelled, factor]	Primary payer/insurance at the time of diagnosis	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	894 ( 42.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 46 ( 2.2% ) 36 ( 1.7% ) 75 ( 3.5% ) 62 ( 2.9% ) 195 ( 9.2% ) 111 ( 5.2% ) 196 ( 9.2% ) 120 ( 5.6% ) 55 ( 2.6% ) 47 ( 2.2% ) 1 ( 0.0% ) 149 ( 7.0% ) 0 ( 0.0% ) 138 ( 6.5% )		42 (1.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	114 ( 60.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.1% ) 0 ( 0.0% ) 7 ( 3.7% ) 6 ( 3.2% ) 14 ( 7.4% ) 1 ( 0.5% ) 23 ( 12.2% ) 4 ( 2.1% ) 4 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 3.7% ) 0 ( 0.0% ) 4 ( 2.1% )		1 (0.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	110 ( 63.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.3% ) 0 ( 0.0% ) 6 ( 3.5% ) 4 ( 2.3% ) 17 ( 9.8% ) 4 ( 2.3% ) 10 ( 5.8% ) 0 ( 0.0% ) 9 ( 5.2% ) 1 ( 0.6% ) 0 ( 0.0% ) 5 ( 2.9% ) 0 ( 0.0% ) 3 ( 1.7% )		1 (0.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	135 ( 57.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.3% ) 1 ( 0.4% ) 11 ( 4.6% ) 11 ( 4.6% ) 15 ( 6.3% ) 21 ( 8.9% ) 14 ( 5.9% ) 2 ( 0.8% ) 4 ( 1.7% ) 4 ( 1.7% ) 0 ( 0.0% ) 3 ( 1.3% ) 0 ( 0.0% ) 13 ( 5.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	56 ( 33.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 3.0% ) 2 ( 1.2% ) 7 ( 4.1% ) 16 ( 9.5% ) 15 ( 8.9% ) 4 ( 2.4% ) 22 ( 13.0% ) 26 ( 15.4% ) 5 ( 3.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 2 ( 1.2% ) 0 ( 0.0% ) 8 ( 4.7% )		5 (2.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	110 ( 39.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 2.1% ) 1 ( 0.4% ) 10 ( 3.6% ) 14 ( 5.0% ) 26 ( 9.3% ) 17 ( 6.0% ) 36 ( 12.8% ) 8 ( 2.8% ) 6 ( 2.1% ) 3 ( 1.1% ) 1 ( 0.4% ) 33 ( 11.7% ) 0 ( 0.0% ) 10 ( 3.6% )		9 (3.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	359 ( 33.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 23 ( 2.2% ) 32 ( 3.0% ) 34 ( 3.2% ) 10 ( 0.9% ) 107 ( 10.1% ) 62 ( 5.8% ) 91 ( 8.6% ) 80 ( 7.5% ) 27 ( 2.5% ) 38 ( 3.6% ) 0 ( 0.0% ) 99 ( 9.3% ) 0 ( 0.0% ) 100 ( 9.4% )		25 (2.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	primary_payer_at_dx [factor]	1. Private_managed.20 2. Not_insured.1 3. Not_insured_self_pay.2 4. Insurance.10 5. Private_FFS.21 6. Medicaid.31 7. Medicaid_managed_care.35 8. Medicare_medicare.60 9. Medicare_suppl.61 10. Medicare_managed_care.62 11. Medicare_private_suppl.63 12. Medicare_medicaid.64 13. TRICARE.65 14. Military.66 15. Veterans_Affairs.67 16. Indian_PHS.68 17. Unknown.99	10 ( 66.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.7% ) 1 ( 6.7% ) 2 ( 13.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1 (6.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SEER SUMMARY STAGE 2000

• Description: Code for summary stage at the initial diagnosis or treatment of the reportable tumor. For hospital registries, CoC requires its use in the absence of a defined AJCC classification. For site-specific definitions of categories, see SEER Summary Staging Manual 2000.

• Summary stage should include all information available through completion of surgery(ies) in the first course of treatment or within 4 months of diagnosis in the absence of disease progression, whichever is longer.

• Rationale: Stage information is important when evaluating the effects of cancer control programs. It is crucial in understanding whether changes over time in incidence rates or outcomes are due to earlier detection of the cancers. In addition, cancer treatment cannot be studied without knowing the stage at diagnosis.

• Codes

  • 0 In situ
  • 1 Localized
  • 2 Regional, direct extension only
  • 3 Regional, regional lymph nodes only
  • 4 Regional, direct extension and regional lymph nodes
  • 5 Regional, NOS
  • 7 Distant
  • 8 Not applicable
  • 9 Unstaged

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#759

All data

st_css() #IMPORTANT!

  seersummarystage2000 <- as.factor(trimws(d[,"seersummarystage2000"]))
  levels(seersummarystage2000)[levels(seersummarystage2000)=="1"] <- "Localized.1"
  levels(seersummarystage2000)[levels(seersummarystage2000)=="2"] <- "Regional_direct_extension.2"
  levels(seersummarystage2000)[levels(seersummarystage2000)=="3"] <- "Regional_lymph_nodes.3"
  levels(seersummarystage2000)[levels(seersummarystage2000)=="4"] <- "Regional_both_23.4"
  levels(seersummarystage2000)[levels(seersummarystage2000)=="5"] <- "Regional_NOS.5"
  levels(seersummarystage2000)[levels(seersummarystage2000)=="7"] <- "Distant.7"
  levels(seersummarystage2000)[levels(seersummarystage2000)=="9"] <- "Unstaged.9"


  new.d <- data.frame(new.d, seersummarystage2000)
  new.d <- apply_labels(new.d, seersummarystage2000 = "seer_summary_stage_2000")

temp.d <- data.frame (new.d.1, seersummarystage2000)
summarytools::view(dfSummary(new.d$seersummarystage2000, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seersummarystage2000 [labelled, factor]	seer_summary_stage_2000	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	1652 ( 78.0% ) 284 ( 13.4% ) 30 ( 1.4% ) 48 ( 2.3% ) 2 ( 0.1% ) 56 ( 2.6% ) 46 ( 2.2% )		49 (2.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	142 ( 75.1% ) 28 ( 14.8% ) 1 ( 0.5% ) 7 ( 3.7% ) 0 ( 0.0% ) 5 ( 2.6% ) 6 ( 3.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	140 ( 80.5% ) 24 ( 13.8% ) 2 ( 1.1% ) 2 ( 1.1% ) 0 ( 0.0% ) 6 ( 3.4% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	170 ( 71.7% ) 36 ( 15.2% ) 7 ( 3.0% ) 11 ( 4.6% ) 0 ( 0.0% ) 9 ( 3.8% ) 4 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	99 ( 69.7% ) 24 ( 16.9% ) 1 ( 0.7% ) 8 ( 5.6% ) 0 ( 0.0% ) 6 ( 4.2% ) 4 ( 2.8% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	206 ( 71.0% ) 65 ( 22.4% ) 5 ( 1.7% ) 5 ( 1.7% ) 0 ( 0.0% ) 4 ( 1.4% ) 5 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	894 ( 82.4% ) 107 ( 9.9% ) 14 ( 1.3% ) 15 ( 1.4% ) 2 ( 0.2% ) 26 ( 2.4% ) 27 ( 2.5% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_2000 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_lymph_nodes.3 4. Regional_both_23.4 5. Regional_NOS.5 6. Distant.7 7. Unstaged.9	1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		15 (93.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SEER SUMMARY STAGE 1977

• Description: Code for summary stage at the initial diagnosis or treatment of the reportable tumor. This has traditionally been used by central registries to monitor time trends. For hospital registries, CoC requires its use in the absence of a defined AJCC classification. For site-specific definitions of categories, see the SEER Summary Staging Guide.

• SEER Summary Stage 1977 is limited to information available within 2 months of the date of diagnosis. NAACCR approved extension of this time period to 4 months for prostate tumors diagnosed beginning January 1, 1995.

• Rationale: Stage information is important when evaluating the effects of cancer control programs. It is crucial for understanding whether changes over time in incidence rates or outcomes are due to earlier detection of the cancers. In addition, cancer treatment cannot be studied without knowing the stage at diagnosis.

• To study historical trends in stage, the coding system must be relatively unchanged (stable) over time. AJCC’s TNM system is updated periodically to maintain clinical relevance with changes in diagnosis and treatment. The surveillance registries often rely on the Summary Stage, which they consider to be more “stable.” Summary Stage has been in widespread use, either as the primary staging scheme or a secondary scheme, in most central and hospital registries since 1977.

• Codes

  • 9 Unstaged
  • 0 In situ
  • 1 Localized
  • 2 Regional, direct extension only
  • 3 Regional, regional lymph nodes only
  • 4 Regional, direct extension and regional lymph nodes
  • 5 Regional, NOS
  • 7 Distant
  • 8 Not applicable

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#760

All data

st_css() #IMPORTANT!

  seersummarystage1977 <- as.factor(trimws(d[,"seersummarystage1977"]))
  levels(seersummarystage1977)[levels(seersummarystage1977)=="1"] <- "Localized.1"
  levels(seersummarystage1977)[levels(seersummarystage1977)=="2"] <- "Regional_direct_extension.2"
  levels(seersummarystage1977)[levels(seersummarystage1977)=="4"] <- "Regional_both.4"
  levels(seersummarystage1977)[levels(seersummarystage1977)=="9"] <- "Unstaged.9"


  new.d <- data.frame(new.d, seersummarystage1977)
  new.d <- apply_labels(new.d, seersummarystage1977 = "seer_summary_stage_1977")

temp.d <- data.frame (new.d.1, seersummarystage1977)
summarytools::view(dfSummary(new.d$seersummarystage1977, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seersummarystage1977 [labelled, factor]	seer_summary_stage_1977	1. Localized.1 2. Regional_direct_extension 3. Regional_both.4 4. Unstaged.9	11 ( 4.6% ) 4 ( 1.7% ) 1 ( 0.4% ) 221 ( 93.2% )		1930 (89.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension.2 3. Regional_both.4 4. Unstaged.9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension.2 3. Regional_both.4 4. Unstaged.9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension 3. Regional_both.4 4. Unstaged.9	11 ( 4.6% ) 4 ( 1.7% ) 1 ( 0.4% ) 221 ( 93.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension.2 3. Regional_both.4 4. Unstaged.9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension.2 3. Regional_both.4 4. Unstaged.9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension.2 3. Regional_both.4 4. Unstaged.9	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	seer_summary_stage_1977 [factor]	1. Localized.1 2. Regional_direct_extension.2 3. Regional_both.4 4. Unstaged.9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SUMMARY STAGE 2018

• Description: Derived Summary Stage 2018 is derived using the EOD data collection system (EOD Primary Tumor [772], EOD Regional Nodes [774] and EOD Mets [776]) algorithm. Other data items may be included in the derivation process. Effective for cases diagnosed 1/1/2018+.

• Rationale: The SEER program has collected staging information on cases since its inception in 1973. Summary Stage groups cases into broad categories of in situ, local, regional, and distant. Summary Stage can be used to evaluate disease spread at diagnosis, treatment patterns and outcomes over time.

• Derived Summary Stage 2018 [762] is only available at the central registry level. Note: This data item was included in Standards Volume II, Version 16; however, it was not implemented until 2018.

• Codes

  • 0 In situ
    
  • 1 Localized
    
  • 2 Regional, direct extension only
    
  • 3 Regional, regional lymph nodes only
    
  • 4 Regional, direct extension and regional lymph nodes
    
  • 7 Distant
    
  • 8 Benign, borderline
    
  • 9 Unknown if extension or metastasis (unstaged, unknown, or unspecified)/Death certificate only case

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#762

All data

  derivedsummarystage2018 <- as.factor(d[,"derivedsummarystage2018"])
  levels(derivedsummarystage2018) <- list(In_situ.0="0",
                                          Localized.1="1",
                                          Regional_direct.2="2",
                                          Regional_regional.3="3",
                                          Regional_direct_regional.4="4",
                                          Distant.7="7",
                                          Benign_borderline.8="8",
                                          Unknown.9="9")
    derivedsummarystage2018 <- relevel(derivedsummarystage2018, ref="Localized.1")
    new.d <- data.frame(new.d, derivedsummarystage2018)
    new.d <- apply_labels(new.d, derivedsummarystage2018 = "Tumor Staging")
    #summary(new.d$derivedsummarystage2018)
temp.d <- data.frame (new.d.1, derivedsummarystage2018)
summarytools::view(dfSummary(new.d$derivedsummarystage2018, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedsummarystage2018 [labelled, factor]	Tumor Staging	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional. 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	28 ( 82.4% ) 0 ( 0.0% ) 3 ( 8.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 8.8% ) 0 ( 0.0% ) 0 ( 0.0% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional.4 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional.4 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional.4 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional. 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	26 ( 81.2% ) 0 ( 0.0% ) 3 ( 9.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 9.4% ) 0 ( 0.0% ) 0 ( 0.0% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional.4 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional. 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	2 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_summary_stage_2018 [factor]	1. Localized.1 2. In_situ.0 3. Regional_direct.2 4. Regional_regional.3 5. Regional_direct_regional.4 6. Distant.7 7. Benign_borderline.8 8. Unknown.9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SUMMARY STAGE 2018

• Description: This item stores the directly assigned Summary Stage 2018. Effective for cases diagnosed 1/1/2018+.
• Rationale: The SEER program has collected staging information on cases since its inception in 1973. Summary Stage groups cases into broad categories of in situ, local, regional, and distant. Summary Stage can be used to evaluate disease spread at diagnosis, treatment patterns and outcomes over time.
• Note: This data item was included in Standards Volume II, Version 16; however, it was not implemented until 2018.
• Codes
  • 0 In situ
  • 1 Localized only
  • 2 Regional by direct extension only
  • 3 Regional lymph nodes only
  • 4 Regional by BOTH direct extension AND lymph node involvement
  • 7 Distant site(s)/node(s) involved
  • 8 Benign/borderline*
  • 9 Unknown if extension or metastasis (unstaged, unknown, or unspecified) Death certificate only case
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#764

All data

st_css() #IMPORTANT!

  summarystage2018 <- as.factor(trimws(d[,"summarystage2018"]))
  levels(summarystage2018)[levels(summarystage2018)=="1"] <- "Localized_only.1"
  levels(summarystage2018)[levels(summarystage2018)=="2"] <- "Regional_direct_extension.2"
  levels(summarystage2018)[levels(summarystage2018)=="7"] <- "Distant_site_node_involved.7"


  new.d <- data.frame(new.d, summarystage2018)
  new.d <- apply_labels(new.d, summarystage2018 = "summary_stage_2018")

temp.d <- data.frame (new.d.1, summarystage2018)
summarytools::view(dfSummary(new.d$summarystage2018, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summarystage2018 [labelled, factor]	summary_stage_2018	1. Localized_only.1 2. Regional_direct_extension 3. Distant_site_node_involve	28 ( 82.4% ) 3 ( 8.8% ) 3 ( 8.8% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension.2 3. Distant_site_node_involved.7	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension.2 3. Distant_site_node_involved.7	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension.2 3. Distant_site_node_involved.7	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension 3. Distant_site_node_involve	26 ( 81.2% ) 3 ( 9.4% ) 3 ( 9.4% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension.2 3. Distant_site_node_involved.7	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension 3. Distant_site_node_involve	2 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	summary_stage_2018 [factor]	1. Localized_only.1 2. Regional_direct_extension.2 3. Distant_site_node_involved.7	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD PRIMARY TUMOR

• Description: EOD Primary Tumor is part of the EOD 2018 data collection system and is used to classify contiguous growth (extension) of the primary tumor within the organ of origin or its direct extension into neighboring organs. See also EOD Regional Nodes [774] and EOD Mets [776]. Effective for cases diagnosed 1/1/2018+.
• Rationale: EOD Primary Tumor is used to calculate Derived EOD 2018 T [785] (when applicable) and Derived Summary Stage 2018 [762]. Derivation will occur at the level of the central registry.
• Note: This data item was included in Standards Volume II, Version 16; however, it was not implemented until 2018.
• Codes (In addition to schema-specific codes where needed)
  • 000 In situ, intraepithelial, noninvasive
  • 800 No evidence of primary tumor
  • 999 Unknown; primary tumor not stated Primary tumor cannot be assessed Not documented in patient record Death certificate only (DCO)
• Codes
  • 100 Incidental histologic finding (for example, on TURP) in 5 percent or less of tissue resected (clinically inapparent)
  • 120 Tumor identified by needle biopsy (clinically inapparent/not palpable)
  • 150 Incidental histologic finding (for example, on TURP), number of foci or percent of involved tissue not specified (clinically inapparent/not palpable)
  • 200 Involves one-half of one side or less
  • 220 Involves both lobes/sides
  • 300 Localized, NOS Not known if clinically apparent or inapparent
  • 350 Bladder neck, microscopic invasion
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#772

All data

st_css() #IMPORTANT!

  eodprimarytumor <- as.factor(trimws(d[,"eodprimarytumor"]))
  levels(eodprimarytumor)[levels(eodprimarytumor)=="100"] <- "5_percent_or_less_tissue.100"
  levels(eodprimarytumor)[levels(eodprimarytumor)=="120"] <- "Identified_by_needle_biopsy.120"
  levels(eodprimarytumor)[levels(eodprimarytumor)=="150"] <- "number_of_foci_not_specified.150"
  levels(eodprimarytumor)[levels(eodprimarytumor)=="200"] <- "one_half.200"
  levels(eodprimarytumor)[levels(eodprimarytumor)=="220"] <- "both_lobes_sides.220"
  levels(eodprimarytumor)[levels(eodprimarytumor)=="300"] <- "Localized_NOS.300"
  levels(eodprimarytumor)[levels(eodprimarytumor)=="350"] <- "Bladder_neck_microscopic_invasion.350"

  new.d <- data.frame(new.d, eodprimarytumor)
  new.d <- apply_labels(new.d, eodprimarytumor = "eod_primary_tumor")

temp.d <- data.frame (new.d.1, eodprimarytumor)
summarytools::view(dfSummary(new.d$eodprimarytumor, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eodprimarytumor [labelled, factor]	eod_primary_tumor	1. 5_percent_or_less_tissue. 2. Identified_by_needle_biop 3. number_of_foci_not_specif 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_	1 ( 2.9% ) 17 ( 50.0% ) 1 ( 2.9% ) 7 ( 20.6% ) 1 ( 2.9% ) 6 ( 17.6% ) 1 ( 2.9% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue.100 2. Identified_by_needle_biopsy.120 3. number_of_foci_not_specified.150 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_invasion.350	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue.100 2. Identified_by_needle_biopsy.120 3. number_of_foci_not_specified.150 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_invasion.350	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue.100 2. Identified_by_needle_biopsy.120 3. number_of_foci_not_specified.150 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_invasion.350	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue. 2. Identified_by_needle_biop 3. number_of_foci_not_specif 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_	1 ( 3.1% ) 16 ( 50.0% ) 1 ( 3.1% ) 6 ( 18.8% ) 1 ( 3.1% ) 6 ( 18.8% ) 1 ( 3.1% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue.100 2. Identified_by_needle_biopsy.120 3. number_of_foci_not_specified.150 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_invasion.350	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue. 2. Identified_by_needle_biop 3. number_of_foci_not_specif 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_	0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_primary_tumor [factor]	1. 5_percent_or_less_tissue.100 2. Identified_by_needle_biopsy.120 3. number_of_foci_not_specified.150 4. one_half.200 5. both_lobes_sides.220 6. Localized_NOS.300 7. Bladder_neck_microscopic_invasion.350	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD REGIONAL NODES

• Description: EOD Regional Nodes is part of the EOD 2018 data collection system and is used to classify the regional lymph nodes involved with cancer at the time of diagnosis. See also EOD Primary Tumor [772] and EOD Mets [776]. Effective for cases diagnosed 1/1/2018+.
• Rationale: EOD Regional Nodes is used to calculate Derived EOD 2018 N [815] (when applicable) and Derived Summary Stage 2018 [762]. Derivation will occur at the level of the central registry. Note: This data item was included in Standards Volume II, Version 16; however, it was not implemented until 2018.
• Codes
  • 000 None
  • 300 Hypogastric/Iliac, NOS/Pelvic, NOS/Pelvic, NOS/Sacral, NOS
  • 800 Regional lymph node(s), NOS Lymph node(s), NOS
  • 888 Not applicable–e.g., CNS, hematopoietic
  • 999 Unknown
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#774

All data

st_css() #IMPORTANT!

  eodregionalnodes <- as.factor(trimws(d[,"eodregionalnodes"]))
  levels(eodregionalnodes)[levels(eodregionalnodes)=="000"] <- "None.100"
  levels(eodregionalnodes)[levels(eodregionalnodes)=="300"] <- "Hypogastric.300"

  new.d <- data.frame(new.d, eodregionalnodes)
  new.d <- apply_labels(new.d, eodregionalnodes = "eod_regional_nodes")

temp.d <- data.frame (new.d.1, eodregionalnodes)
summarytools::view(dfSummary(new.d$eodregionalnodes, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eodregionalnodes [labelled, factor]	eod_regional_nodes	1. None.100 2. Hypogastric.300	33 ( 97.1% ) 1 ( 2.9% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	31 ( 96.9% ) 1 ( 3.1% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	2 ( 100.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_regional_nodes [factor]	1. None.100 2. Hypogastric.300	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD METS

• Description: EOD Mets is part of the EOD 2018 data collection system and is used to classify the distant site(s) of metastatic involvement at time of diagnosis. See also EOD Primary Tumor [772] and EOD Regional Nodes [774]. Effective for cases diagnosed 1/1/2018+.
• Rationale: EOD Mets is used to calculate Derived EOD 2018 M [795] (when applicable) and Derived Summary Stage 2018 [762]. Derivation will occur at the level of the central registry.
• Note: This data item was included in Standards Volume II, Version 16; however, it was not implemented until 2018.
• Codes
  • 00 None No distant metastasis Unknown if distant metastasis
  • 30 Bone WITH or WITHOUT distant lymph node(s)
  • 50 Other specified distant metastasis/WITH or WITHOUT distant lymph node(s) or bone metastasis/Carcinomatosis
  • 88 Not applicable: Information not collected for this schema Use for these sites only: HemeRetic; Ill Defined Other (includes unknown primary site); Kaposi Sarcoma; Lymphoma; Lymphoma-CLL/SLL; Myeloma Plasma Cell Disorder
  • 99 Death certificate only (DCO)
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#776

All data

st_css() #IMPORTANT!

  eodmets <- as.factor(trimws(d[,"eodmets"]))
  levels(eodmets)[levels(eodmets)=="00"] <- "None.100"
  levels(eodmets)[levels(eodmets)=="30"] <- "Bone_WITH_or_WITHOUT.30"
  levels(eodmets)[levels(eodmets)=="50"] <- "Other_specified_metastasis.50"

  new.d <- data.frame(new.d, eodmets)
  new.d <- apply_labels(new.d, eodmets = "eod_mets")
temp.d <- data.frame (new.d.1, eodmets)
summarytools::view(dfSummary(new.d$eodmets), style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE, method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eodmets [labelled, factor]	eod_mets	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasi	31 ( 91.2% ) 2 ( 5.9% ) 1 ( 2.9% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasis.50	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasis.50	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasis.50	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasi	29 ( 90.6% ) 2 ( 6.2% ) 1 ( 3.1% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasis.50	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasi	2 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eod_mets [factor]	1. None.100 2. Bone_WITH_or_WITHOUT.30 3. Other_specified_metastasis.50	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD–EXTENSION

• Description: Part of the 10-digit EOD [779]. Detailed site-specific codes for anatomic EOD used by SEER for tumors diagnosed from January 1, 1988, through December 31, 2003.

• Codes were revised effective January 1, 1998, to reflect changes in the AJCC Cancer Staging Manual, Fifth Edition.

• Rationale: Site-specific EOD codes provide extensive detail describing disease extent. The EOD codes can be grouped into different stage categories for analysis (e.g., historical summary stage categories consistent with those used in published SEER data since 1973, or more recently, AJCC stage groupings). The codes are updated as needed, but updates are usually backward compatible with old categories. See Comparative Staging Guide for Cancer6.

• Codes (See SEER Extent of Disease, 1988: Codes and Coding Instructions, Third Edition8 for site-specific codes and coding rules for all EOD fields.)

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#790

All data

st_css() #IMPORTANT!

  eodextension <- as.factor(trimws(d[,"eodextension"]))

  new.d <- data.frame(new.d, eodextension)
  new.d <- apply_labels(new.d, eodextension = "eod_extension")
temp.d <- data.frame (new.d.1, eodextension)
summarytools::view(dfSummary(new.d$eodextension), style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE, method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eodextension [labelled, factor]	eod_extension	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD–EXTENSION PROST PATH

• Description: Part of the 10-digit EOD [779]. Detailed site-specific codes for anatomic EOD used by SEER for tumors diagnosed from January 1, 1988, through December 31, 2003.

• Codes were revised effective January 1, 1998, to reflect changes in the AJCC Cancer Staging Manual, Fifth Edition.

• Rationale: Site-specific EOD codes provide extensive detail describing disease extent. The EOD codes can be grouped into different stage categories for analysis (e.g., historical summary stage categories consistent with those used in published SEER data since 1973, or more recently, AJCC stage groupings). The codes are updated as needed, but updates are usually backward compatible with old categories. See Comparative Staging Guide for Cancer.

• EOD–Extension Prost Path is an additional field for prostate cancer only to reflect information from radical prostatectomy, effective for January 1, 1995, through December 31, 2003, diagnoses. The field is left blank for all other primaries.

• Codes (See SEER Extent of Disease, 1988: Codes and Coding Instructions, Third Edition8 for site-specific codes and coding rules for all EOD fields.)

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#800

All data

st_css() #IMPORTANT!

  eodextensionprostpath <- as.factor(trimws(d[,"eodextensionprostpath"]))

  new.d <- data.frame(new.d, eodextensionprostpath)
  new.d <- apply_labels(new.d, eodextensionprostpath = "eod_extension_prost_path")
temp.d <- data.frame (new.d.1, eodextensionprostpath)
summarytools::view(dfSummary(new.d$eodextensionprostpath), style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE, method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eodextensionprostpath [labelled, factor]	eod_extension_prost_path	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD–LYMPH NODE INVOLV

• Description: Part of the 10-digit EOD [779]. Detailed site-specific codes for anatomic EOD used by SEER for tumors diagnosed from January 1, 1988, through December 31, 2003.

• Codes were revised effective January 1, 1998, to reflect changes in the AJCC Cancer Staging Manual, Fifth Edition.

• Rationale: Site-specific EOD codes provide extensive detail describing disease extent. The EOD codes can be grouped into different stage categories for analysis (e.g., historical summary stage categories consistent with those used in published SEER data since 1973, or more recently, AJCC stage groupings). The codes are updated as needed, but updates are usually backward compatible with old categories. See Comparative Staging Guide for Cancer.

• Codes (See SEER Extent of Disease, 1988: Codes and Coding Instructions, Third Edition8 for site-specific codes and coding rules for all EOD fields.)

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#810

All data

st_css() #IMPORTANT!

  eodlymphnodeinvolv <- as.factor(trimws(d[,"eodlymphnodeinvolv"]))

  new.d <- data.frame(new.d, eodlymphnodeinvolv)
  new.d <- apply_labels(new.d, eodlymphnodeinvolv = "eod_lymph_node_involv")
temp.d <- data.frame (new.d.1, eodlymphnodeinvolv)
summarytools::view(dfSummary(new.d$eodlymphnodeinvolv), style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE, method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	eodlymphnodeinvolv [labelled, factor]	eod_lymph_node_involv	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED EOD 2018 STAGE GROUP

• Description: Derived EOD 2018 Stage Group is derived using the EOD data collection system (EOD Primary Tumor [772], EOD Regional Nodes [774] and EOD Mets [776]) algorithm. Other data items may be included in the derivation process. Effective for cases diagnosed 1/1/2018+.

• Rationale: Derived EOD 2018 Stage Group can be used to evaluate disease spread at diagnosis, treatment patterns and outcomes over time.

• Derived EOD 2018 Stage group is only available at the central registry level.

• Codes: See the most current version of EOD (https://staging.seer.cancer.gov/) for rules and site-specific codes and coding structures.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#818

All data

  derivedeod2018stagegroup <- as.factor(trimws(d[,"derivedeod2018stagegroup"]))
  # THIS CODING NEEDS TO BE CONFIRMED
  levels(derivedeod2018stagegroup) <- list(T.1="1",
                                          T.1B="1B",
                                          T.2A="2A",
                                          T.2B="2B",
                                          T.2C="2C",
                                          T.3="3",
                                          T.3A="3A",
                                          T.3B="3B",
                                          T.3C="3C",
                                          T.4="4",
                                          T.4A="4A",
                                          T.4B="4B",
                                          Do_Not_Know.88="88",
                                          Unknown.99="99")
    derivedeod2018stagegroup <- relevel(derivedeod2018stagegroup, ref="T.1")
    new.d <- data.frame(new.d, derivedeod2018stagegroup)
    new.d <- apply_labels(new.d, derivedeod2018stagegroup = "Tumor Stage Group")
    #summary(new.d$derivedeod2018stagegroup)
temp.d <- data.frame (new.d.1, derivedeod2018stagegroup)
summarytools::view(dfSummary(new.d$derivedeod2018stagegroup, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedeod2018stagegroup [labelled, factor]	Tumor Stage Group	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	2 ( 5.9% ) 1 ( 2.9% ) 2 ( 5.9% ) 7 ( 20.6% ) 11 ( 32.4% ) 0 ( 0.0% ) 2 ( 5.9% ) 2 ( 5.9% ) 2 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 8.8% ) 0 ( 0.0% ) 2 ( 5.9% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	1 ( 3.1% ) 0 ( 0.0% ) 2 ( 6.2% ) 7 ( 21.9% ) 11 ( 34.4% ) 0 ( 0.0% ) 2 ( 6.2% ) 2 ( 6.2% ) 2 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 9.4% ) 0 ( 0.0% ) 2 ( 6.2% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	1 ( 50.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_eod_2018_stage_group [factor]	1. T.1 2. T.1B 3. T.2A 4. T.2B 5. T.2C 6. T.3 7. T.3A 8. T.3B 9. T.3C 10. T.4 11. T.4A 12. T.4B 13. Do_Not_Know.88 14. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

REGIONAL NODES POSITIVE

• Description: Records the exact number of regional nodes examined by the pathologist and found to contain metastases. Beginning with tumors diagnosed on or after January 1, 2004, this item is a component of the Collaborative Stage system. For tumors diagnosed from 1988 through 2003, this item was part of the 10-digit EOD [779], detailed site-specific codes for anatomic EOD.
• Rationale: This data item is necessary for pathologic staging, and it serves as a quality measure for pathology reports and the extent of the surgical evaluation and treatment of the patient.
• Codes
  • 00 All nodes examined are negative
  • 01-89 1-89 nodes are positive (code exact number of nodes positive)
  • 90 90 or more nodes are positive
  • 95 Positive aspiration of lymph node(s) was performed
  • 97 Positive nodes are documented, but the number is unspecified
  • 98 No nodes were examined
  • 99 It is unknown whether nodes are positive; not applicable; not stated in patient record
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#820

All data

st_css() #IMPORTANT!

  regionalnodespositive <- as.factor(trimws(d[,"regionalnodespositive"]))
  levels(regionalnodespositive)[levels(regionalnodespositive)=="0"] <- "All_negative.0"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="1"] <- "1_node_posi.1"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="2"] <- "2_nodes_posi.2"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="3"] <- "3_nodes_posi.3"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="4"] <- "4_nodes_posi.4"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="5"] <- "5_nodes_posi.5"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="6"] <- "6_nodes_posi.6"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="18"] <- "18_nodes_posi.18"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="19"] <- "19_nodes_posi.19"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="95"] <- "Positive_aspiration.95"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="98"] <- "No_nodes_examined.98"
  levels(regionalnodespositive)[levels(regionalnodespositive)=="99"] <- "Unknown.99"

  new.d <- data.frame(new.d, regionalnodespositive)
  new.d <- apply_labels(new.d, regionalnodespositive = "regional_nodes_positive")

temp.d <- data.frame (new.d.1, regionalnodespositive)
summarytools::view(dfSummary(new.d$regionalnodespositive, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regionalnodespositive [labelled, factor]	regional_nodes_positive	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	659 ( 30.4% ) 30 ( 1.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 13 ( 0.6% ) 5 ( 0.2% ) 4 ( 0.2% ) 2 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 1418 ( 65.4% ) 30 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	59 ( 31.2% ) 4 ( 2.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 122 ( 64.6% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	35 ( 20.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 136 ( 78.2% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	102 ( 43.0% ) 4 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 1.7% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.8% ) 121 ( 51.1% ) 3 ( 1.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	62 ( 35.6% ) 3 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.6% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 101 ( 58.0% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	159 ( 54.8% ) 5 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 120 ( 41.4% ) 3 ( 1.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	237 ( 21.8% ) 13 ( 1.2% ) 0 ( 0.0% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 807 ( 74.2% ) 21 ( 1.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_positive [factor]	1. All_negative.0 2. 1_node_posi.1 3. 18_nodes_posi.18 4. 19_nodes_posi.19 5. 2_nodes_posi.2 6. 3_nodes_posi.3 7. 4_nodes_posi.4 8. 5_nodes_posi.5 9. 6_nodes_posi.6 10. Positive_aspiration.95 11. No_nodes_examined.98 12. Unknown.99	5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 68.8% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

REGIONAL NODES EXAMINED

• Description: Records the total number of regional lymph nodes that were removed and examined by the pathologist. Beginning with tumors diagnosed on or after January 1, 2004, this item is a component of the Collaborative Stage system.
• Rationale: This data item serves as a quality measure of the pathologic and surgical evaluation and treatment of the patient.
• Codes
  • 00 No nodes were examined
  • 01-89 1-89 nodes were examined (code the exact number of regional lymph nodes examined)
  • 90 90 or more nodes were examined
  • 95 No regional nodes were removed, but aspiration of regional nodes was performed
  • 96 Regional lymph node removal was documented as a sampling, and the number of nodes is unknown/not stated
  • 97 Regional lymph node removal was documented as a dissection, and the number of nodes is unknown/not stated
  • 98 Regional lymph nodes were surgically removed, but the number of lymph nodes is unknown/not stated and not documented as a sampling or dissection; nodes were examined, but the number is unknown
  • 99 It is unknown whether nodes were examined; not stated in patient record
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#830

All data

st_css() #IMPORTANT!

  regionalnodesexamined <- as.factor(trimws(d[,"regionalnodesexamined"]))
  levels(regionalnodesexamined)[levels(regionalnodesexamined)=="0"] <- "No_nodes_examined.0"
  levels(regionalnodesexamined)[levels(regionalnodesexamined)=="95"] <- "No_removed_aspiration_performed.95"
  levels(regionalnodesexamined)[levels(regionalnodesexamined)=="97"] <- "dissection_number_unknown.97"
  levels(regionalnodesexamined)[levels(regionalnodesexamined)=="98"] <- "nodes_removed_number_unknown.98"
  levels(regionalnodesexamined)[levels(regionalnodesexamined)=="99"] <- "Unknown.99"

  new.d <- data.frame(new.d, regionalnodesexamined)
  new.d <- apply_labels(new.d, regionalnodesexamined = "regional_nodes_examined")

temp.d <- data.frame (new.d.1, regionalnodesexamined)
summarytools::view(dfSummary(new.d$regionalnodesexamined, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regionalnodesexamined [labelled, factor]	regional_nodes_examined	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	1418 ( 65.4% ) 29 ( 1.3% ) 37 ( 1.7% ) 27 ( 1.2% ) 20 ( 0.9% ) 22 ( 1.0% ) 17 ( 0.8% ) 11 ( 0.5% ) 15 ( 0.7% ) 5 ( 0.2% ) 8 ( 0.4% ) 9 ( 0.4% ) 92 ( 4.2% ) 8 ( 0.4% ) 4 ( 0.2% ) 8 ( 0.4% ) 5 ( 0.2% ) 4 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 4 ( 0.2% ) 67 ( 3.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 58 ( 2.7% ) 1 ( 0.0% ) 1 ( 0.0% ) 73 ( 3.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 42 ( 1.9% ) 48 ( 2.2% ) 39 ( 1.8% ) 33 ( 1.5% ) 4 ( 0.2% ) 4 ( 0.2% ) 3 ( 0.1% ) 30 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	122 ( 64.6% ) 2 ( 1.1% ) 3 ( 1.6% ) 6 ( 3.2% ) 2 ( 1.1% ) 1 ( 0.5% ) 3 ( 1.6% ) 1 ( 0.5% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 3 ( 1.6% ) 2 ( 1.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 5 ( 2.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 4.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.6% ) 7 ( 3.7% ) 1 ( 0.5% ) 4 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	136 ( 78.2% ) 0 ( 0.0% ) 1 ( 0.6% ) 2 ( 1.1% ) 3 ( 1.7% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 6 ( 3.4% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.7% ) 2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	121 ( 51.1% ) 3 ( 1.3% ) 7 ( 3.0% ) 6 ( 2.5% ) 4 ( 1.7% ) 5 ( 2.1% ) 4 ( 1.7% ) 3 ( 1.3% ) 2 ( 0.8% ) 2 ( 0.8% ) 3 ( 1.3% ) 3 ( 1.3% ) 12 ( 5.1% ) 2 ( 0.8% ) 2 ( 0.8% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 11 ( 4.6% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 8 ( 3.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 9 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.1% ) 4 ( 1.7% ) 2 ( 0.8% ) 6 ( 2.5% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 3 ( 1.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	101 ( 58.0% ) 1 ( 0.6% ) 5 ( 2.9% ) 2 ( 1.1% ) 3 ( 1.7% ) 5 ( 2.9% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 4 ( 2.3% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.9% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 6.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 4 ( 2.3% ) 5 ( 2.9% ) 7 ( 4.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	120 ( 41.4% ) 8 ( 2.8% ) 7 ( 2.4% ) 3 ( 1.0% ) 1 ( 0.3% ) 3 ( 1.0% ) 2 ( 0.7% ) 2 ( 0.7% ) 0 ( 0.0% ) 2 ( 0.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 30 ( 10.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 24 ( 8.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 19 ( 6.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 18 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 14 ( 4.8% ) 11 ( 3.8% ) 13 ( 4.5% ) 4 ( 1.4% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 3 ( 1.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	807 ( 74.2% ) 14 ( 1.3% ) 14 ( 1.3% ) 8 ( 0.7% ) 7 ( 0.6% ) 7 ( 0.6% ) 6 ( 0.6% ) 3 ( 0.3% ) 9 ( 0.8% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 36 ( 3.3% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 0.4% ) 20 ( 1.8% ) 0 ( 0.0% ) 1 ( 0.1% ) 2 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 18 ( 1.7% ) 1 ( 0.1% ) 0 ( 0.0% ) 23 ( 2.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 15 ( 1.4% ) 20 ( 1.8% ) 15 ( 1.4% ) 11 ( 1.0% ) 2 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.2% ) 21 ( 1.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	regional_nodes_examined [factor]	1. No_nodes_examined.0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 22 17. 23 18. 24 19. 25 20. 26 21. 27 22. 29 23. 3 24. 30 25. 32 26. 33 27. 34 28. 35 29. 36 30. 37 31. 39 32. 4 33. 42 34. 46 35. 5 36. 50 37. 51 38. 52 39. 6 40. 7 41. 8 42. 9 43. No_removed_aspiration_per 44. dissection_number_unknown 45. nodes_removed_number_unkn 46. Unknown.99	11 ( 68.8% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM PATH T

• Description: Detailed site-specific codes for the pathologic tumor (T) as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual. This field is left blank if no information at all is available to code this item.

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#880

All data

st_css() #IMPORTANT!

  tnmpatht <- as.factor(trimws(d[,"tnmpatht"]))
  levels(tnmpatht)[levels(tnmpatht)=="88"] <- "Not_applicable.88"

  new.d <- data.frame(new.d, tnmpatht)
  new.d <- apply_labels(new.d, tnmpatht = "tnm_path_t")

temp.d <- data.frame (new.d.1, tnmpatht)
summarytools::view(dfSummary(new.d$tnmpatht, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmpatht [labelled, factor]	tnm_path_t	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	1 ( 0.1% ) 1 ( 0.1% ) 15 ( 1.5% ) 11 ( 1.1% ) 2 ( 0.2% ) 118 ( 12.0% ) 24 ( 2.4% ) 21 ( 2.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 23 ( 2.3% ) 26 ( 2.6% ) 7 ( 0.7% ) 360 ( 36.6% ) 3 ( 0.3% ) 118 ( 12.0% ) 76 ( 7.7% ) 2 ( 0.2% ) 103 ( 10.5% ) 71 ( 7.2% )		1183 (54.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.5% ) 4 ( 5.9% ) 2 ( 2.9% ) 36 ( 52.9% ) 0 ( 0.0% ) 8 ( 11.8% ) 9 ( 13.2% ) 0 ( 0.0% ) 8 ( 11.8% ) 0 ( 0.0% )		121 (64.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.8% ) 0 ( 0.0% ) 4 ( 7.3% ) 0 ( 0.0% ) 14 ( 25.5% ) 1 ( 1.8% ) 13 ( 23.6% ) 4 ( 7.3% ) 0 ( 0.0% ) 18 ( 32.7% ) 0 ( 0.0% )		119 (68.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.0% ) 2 ( 2.0% ) 0 ( 0.0% ) 65 ( 64.4% ) 1 ( 1.0% ) 19 ( 18.8% ) 6 ( 5.9% ) 0 ( 0.0% ) 6 ( 5.9% ) 0 ( 0.0% )		136 (57.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.8% ) 1 ( 1.4% ) 16 ( 22.2% ) 4 ( 5.6% ) 2 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.8% ) 1 ( 1.4% ) 0 ( 0.0% ) 22 ( 30.6% ) 0 ( 0.0% ) 11 ( 15.3% ) 9 ( 12.5% ) 0 ( 0.0% ) 1 ( 1.4% ) 1 ( 1.4% )		102 (58.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 4 ( 2.1% ) 1 ( 0.5% ) 37 ( 19.6% ) 9 ( 4.8% ) 6 ( 3.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 4 ( 2.1% ) 1 ( 0.5% ) 62 ( 32.8% ) 1 ( 0.5% ) 30 ( 15.9% ) 15 ( 7.9% ) 1 ( 0.5% ) 6 ( 3.2% ) 10 ( 5.3% )		101 (34.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	1 ( 0.2% ) 1 ( 0.2% ) 14 ( 2.9% ) 5 ( 1.0% ) 0 ( 0.0% ) 61 ( 12.4% ) 10 ( 2.0% ) 13 ( 2.6% ) 1 ( 0.2% ) 0 ( 0.0% ) 17 ( 3.5% ) 11 ( 2.2% ) 4 ( 0.8% ) 161 ( 32.8% ) 0 ( 0.0% ) 37 ( 7.5% ) 33 ( 6.7% ) 1 ( 0.2% ) 64 ( 13.0% ) 57 ( 11.6% )		596 (54.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_t [factor]	1. 1B 2. 1C 3. 2 4. 2A 5. 2B 6. 2C 7. 3A 8. 3B 9. Not_applicable.88 10. p0 11. p2 12. p2A 13. p2B 14. p2C 15. p3 16. p3A 17. p3B 18. p4 19. pX 20. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 50.0% ) 1 ( 12.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 37.5% )		8 (50.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM PATH N

• Description: Detailed site-specific codes for the pathologic nodes (N) as defined by AJCC and recorded by physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual. This field is left blank if no information at all is available to code this item.

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#890

All data

st_css() #IMPORTANT!

  tnmpathn <- as.factor(trimws(d[,"tnmpathn"]))
  levels(tnmpathn)[levels(tnmpathn)=="88"] <- "Not_applicable.88"

  new.d <- data.frame(new.d, tnmpathn)
  new.d <- apply_labels(new.d, tnmpathn = "tnm_path_n")

temp.d <- data.frame (new.d.1, tnmpathn)
summarytools::view(dfSummary(new.d$tnmpathn, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmpathn [labelled, factor]	tnm_path_n	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	154 ( 19.6% ) 9 ( 1.1% ) 1 ( 0.1% ) 71 ( 9.0% ) 285 ( 36.2% ) 27 ( 3.4% ) 163 ( 20.7% ) 77 ( 9.8% )		1380 (63.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.9% ) 35 ( 51.5% ) 6 ( 8.8% ) 25 ( 36.8% ) 0 ( 0.0% )		121 (64.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 7.1% ) 31 ( 55.4% ) 2 ( 3.6% ) 19 ( 33.9% ) 0 ( 0.0% )		118 (67.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 74 ( 75.5% ) 4 ( 4.1% ) 19 ( 19.4% ) 0 ( 0.0% )		139 (58.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	24 ( 96.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		149 (85.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	52 ( 94.5% ) 3 ( 5.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		235 (81.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	73 ( 15.2% ) 5 ( 1.0% ) 1 ( 0.2% ) 64 ( 13.3% ) 145 ( 30.2% ) 15 ( 3.1% ) 100 ( 20.8% ) 77 ( 16.0% )		607 (55.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_n [factor]	1. 0 2. 1 3. Not_applicable.88 4. c0 5. p0 6. p1 7. pX 8. X	5 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		11 (68.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM PATH M

• Description: Detailed site-specific codes for the pathologic metastases (M) as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual. This field is left blank if no information at all is available to code this item.

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#900

All data

st_css() #IMPORTANT!

  tnmpathm <- as.factor(trimws(d[,"tnmpathm"]))
  levels(tnmpathm)[levels(tnmpathm)=="88"] <- "Not_applicable.88"

  new.d <- data.frame(new.d, tnmpathm)
  new.d <- apply_labels(new.d, tnmpathm = "tnm_path_m")

temp.d <- data.frame (new.d.1, tnmpathm)
summarytools::view(dfSummary(new.d$tnmpathm, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmpathm [labelled, factor]	tnm_path_m	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	1 ( 0.2% ) 1 ( 0.2% ) 562 ( 98.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% )		1596 (73.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	0 ( 0.0% ) 0 ( 0.0% ) 42 ( 97.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% )		146 (77.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	0 ( 0.0% ) 0 ( 0.0% ) 33 ( 97.1% ) 1 ( 2.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		140 (80.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	0 ( 0.0% ) 0 ( 0.0% ) 67 ( 98.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.5% )		169 (71.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	1 ( 2.3% ) 0 ( 0.0% ) 41 ( 95.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% )		131 (75.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	0 ( 0.0% ) 0 ( 0.0% ) 116 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		174 (60.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	0 ( 0.0% ) 1 ( 0.4% ) 263 ( 98.5% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% )		820 (75.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_m [factor]	1. 0 2. Not_applicable.88 3. c0 4. c1 5. c1A 6. c1B 7. p1A 8. p1B 9. p1C	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM PATH STAGE GROUP

• Description: Detailed site-specific codes for the pathologic stage group as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • 99 Unknown, unstaged

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#910

All data

st_css() #IMPORTANT!

  tnmpathstagegroup <- as.factor(trimws(d[,"tnmpathstagegroup"]))
  levels(tnmpathstagegroup)[levels(tnmpathstagegroup)=="99"] <- "Unknown.99"

  new.d <- data.frame(new.d, tnmpathstagegroup)
  new.d <- apply_labels(new.d, tnmpathstagegroup = "tnm_path_stage_group")

temp.d <- data.frame (new.d.1, tnmpathstagegroup)
summarytools::view(dfSummary(new.d$tnmpathstagegroup, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmpathstagegroup [labelled, factor]	tnm_path_stage_group	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	10 ( 0.8% ) 6 ( 0.5% ) 5 ( 0.4% ) 36 ( 2.7% ) 182 ( 13.8% ) 55 ( 4.2% ) 1027 ( 77.7% )		846 (39.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	1 ( 1.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 7.7% ) 7 ( 6.7% ) 87 ( 83.7% )		85 (45.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 15 ( 13.9% ) 3 ( 2.8% ) 90 ( 83.3% )		66 (37.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 21 ( 22.1% ) 5 ( 5.3% ) 68 ( 71.6% )		142 (59.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	0 ( 0.0% ) 0 ( 0.0% ) 5 ( 4.0% ) 32 ( 25.4% ) 18 ( 14.3% ) 9 ( 7.1% ) 62 ( 49.2% )		48 (27.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	2 ( 1.2% ) 3 ( 1.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 54 ( 32.5% ) 8 ( 4.8% ) 99 ( 59.6% )		124 (42.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	6 ( 0.8% ) 2 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 65 ( 9.1% ) 23 ( 3.2% ) 617 ( 86.5% )		374 (34.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_path_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 44.4% ) 1 ( 11.1% ) 0 ( 0.0% ) 4 ( 44.4% )		7 (43.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM CLIN T

• Description: Detailed site-specific codes for the clinical tumor (T) as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual. This field is left blank if no information at all is available to code this item.

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#940

All data

st_css() #IMPORTANT!

  tnmclint <- as.factor(trimws(d[,"tnmclint"]))
  levels(tnmclint)[levels(tnmclint)=="88"] <- "Not_applicable.88"

  new.d <- data.frame(new.d, tnmclint)
  new.d <- apply_labels(new.d, tnmclint = "tnm_clin_t")

temp.d <- data.frame (new.d.1, tnmclint)
summarytools::view(dfSummary(new.d$tnmclint, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmclint [labelled, factor]	tnm_clin_t	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 316 ( 17.4% ) 24 ( 1.3% ) 15 ( 0.8% ) 9 ( 0.5% ) 18 ( 1.0% ) 2 ( 0.1% ) 4 ( 0.2% ) 5 ( 0.3% ) 5 ( 0.3% ) 22 ( 1.2% ) 4 ( 0.2% ) 2 ( 0.1% ) 1028 ( 56.5% ) 59 ( 3.2% ) 76 ( 4.2% ) 46 ( 2.5% ) 82 ( 4.5% ) 7 ( 0.4% ) 19 ( 1.0% ) 24 ( 1.3% ) 5 ( 0.3% ) 28 ( 1.5% ) 13 ( 0.7% )		348 (16.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.8% ) 1 ( 0.8% ) 0 ( 0.0% ) 87 ( 70.2% ) 6 ( 4.8% ) 7 ( 5.6% ) 4 ( 3.2% ) 10 ( 8.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 2.4% ) 1 ( 0.8% ) 4 ( 3.2% ) 0 ( 0.0% )		65 (34.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 97 ( 68.8% ) 2 ( 1.4% ) 17 ( 12.1% ) 6 ( 4.3% ) 13 ( 9.2% ) 1 ( 0.7% ) 1 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.7% ) 2 ( 1.4% ) 0 ( 0.0% )		33 (19.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.2% ) 1 ( 0.6% ) 1 ( 0.6% ) 105 ( 64.8% ) 9 ( 5.6% ) 13 ( 8.0% ) 5 ( 3.1% ) 16 ( 9.9% ) 1 ( 0.6% ) 2 ( 1.2% ) 3 ( 1.9% ) 0 ( 0.0% ) 4 ( 2.5% ) 0 ( 0.0% )		75 (31.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 24 ( 18.2% ) 5 ( 3.8% ) 1 ( 0.8% ) 1 ( 0.8% ) 2 ( 1.5% ) 0 ( 0.0% ) 1 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 56 ( 42.4% ) 10 ( 7.6% ) 4 ( 3.0% ) 10 ( 7.6% ) 7 ( 5.3% ) 0 ( 0.0% ) 2 ( 1.5% ) 1 ( 0.8% ) 1 ( 0.8% ) 4 ( 3.0% ) 1 ( 0.8% )		42 (24.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 73 ( 25.9% ) 10 ( 3.5% ) 3 ( 1.1% ) 2 ( 0.7% ) 3 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 4 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 126 ( 44.7% ) 16 ( 5.7% ) 10 ( 3.5% ) 5 ( 1.8% ) 5 ( 1.8% ) 0 ( 0.0% ) 6 ( 2.1% ) 5 ( 1.8% ) 1 ( 0.4% ) 7 ( 2.5% ) 2 ( 0.7% )		8 (2.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 2 ( 0.2% ) 211 ( 21.8% ) 9 ( 0.9% ) 11 ( 1.1% ) 6 ( 0.6% ) 13 ( 1.3% ) 2 ( 0.2% ) 2 ( 0.2% ) 5 ( 0.5% ) 4 ( 0.4% ) 13 ( 1.3% ) 2 ( 0.2% ) 0 ( 0.0% ) 556 ( 57.6% ) 16 ( 1.7% ) 25 ( 2.6% ) 16 ( 1.7% ) 31 ( 3.2% ) 5 ( 0.5% ) 8 ( 0.8% ) 12 ( 1.2% ) 1 ( 0.1% ) 7 ( 0.7% ) 7 ( 0.7% )		121 (11.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_t [factor]	1. 0 2. 1 3. 1A 4. 1B 5. 1C 6. 2 7. 2A 8. 2B 9. 2C 10. 3 11. 3A 12. 3B 13. 4 14. c1 15. c1A 16. c1B 17. c1C 18. c2 19. c2A 20. c2B 21. c2C 22. c3 23. c3A 24. c3B 25. c4 26. cX 27. X	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 66.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 8.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 25.0% )		4 (25.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM CLIN N

• Description: Detailed site-specific codes for the clinical nodes (N) as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual. This field is left blank if no information at all is available to code this item.

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#950

All data

st_css() #IMPORTANT!

  tnmclinn <- as.factor(trimws(d[,"tnmclinn"]))
  levels(tnmclinn)[levels(tnmclinn)=="88"] <- "Not_applicable.88"

  new.d <- data.frame(new.d, tnmclinn)
  new.d <- apply_labels(new.d, tnmclinn = "tnm_clin_n")

temp.d <- data.frame (new.d.1, tnmclinn)
summarytools::view(dfSummary(new.d$tnmclinn, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmclinn [labelled, factor]	tnm_clin_n	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	396 ( 26.0% ) 8 ( 0.5% ) 1050 ( 69.0% ) 32 ( 2.1% ) 23 ( 1.5% ) 12 ( 0.8% )		646 (29.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	0 ( 0.0% ) 0 ( 0.0% ) 116 ( 93.5% ) 3 ( 2.4% ) 5 ( 4.0% ) 0 ( 0.0% )		65 (34.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	0 ( 0.0% ) 0 ( 0.0% ) 135 ( 95.7% ) 5 ( 3.5% ) 1 ( 0.7% ) 0 ( 0.0% )		33 (19.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	0 ( 0.0% ) 0 ( 0.0% ) 144 ( 90.0% ) 12 ( 7.5% ) 4 ( 2.5% ) 0 ( 0.0% )		77 (32.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	34 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		140 (80.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	96 ( 99.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		193 (66.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	258 ( 27.0% ) 7 ( 0.7% ) 655 ( 68.4% ) 12 ( 1.3% ) 13 ( 1.4% ) 12 ( 1.3% )		130 (12.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_n [factor]	1. 0 2. 1 3. c0 4. c1 5. cX 6. X	8 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		8 (50.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM CLIN M

• Description: Detailed site-specific codes for the clinical metastases (M) as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual. This field is left blank if no information at all is available to code this item.

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#960

All data

st_css() #IMPORTANT!

  tnmclinm <- as.factor(trimws(d[,"tnmclinm"]))
  levels(tnmclinm)[levels(tnmclinm)=="88"] <- "Not_applicable.88"

  new.d <- data.frame(new.d, tnmclinm)
  new.d <- apply_labels(new.d, tnmclinm = "tnm_clin_m")

temp.d <- data.frame (new.d.1, tnmclinm)
summarytools::view(dfSummary(new.d$tnmclinm, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmclinm [labelled, factor]	tnm_clin_m	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	385 ( 25.8% ) 2 ( 0.1% ) 5 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.1% ) 1061 ( 71.1% ) 9 ( 0.6% ) 3 ( 0.2% ) 20 ( 1.3% ) 3 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% )		674 (31.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 118 ( 96.7% ) 0 ( 0.0% ) 1 ( 0.8% ) 3 ( 2.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		67 (35.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 132 ( 95.7% ) 2 ( 1.4% ) 0 ( 0.0% ) 3 ( 2.2% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% )		36 (20.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 149 ( 94.3% ) 3 ( 1.9% ) 1 ( 0.6% ) 3 ( 1.9% ) 2 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% )		79 (33.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	30 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		144 (82.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	89 ( 98.9% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		200 (69.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	258 ( 27.3% ) 1 ( 0.1% ) 5 ( 0.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 662 ( 70.0% ) 4 ( 0.4% ) 1 ( 0.1% ) 11 ( 1.2% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% )		141 (13.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_m [factor]	1. 0 2. 1 3. 1B 4. 1C 5. Not_applicable.88 6. c0 7. c1 8. c1A 9. c1B 10. c1C 11. p1A 12. p1B	8 ( 88.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		7 (43.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TNM CLIN STAGE GROUP

• Description: Detailed site-specific codes for the clinical stage group as defined by AJCC and recorded by the physician.

• Pathologic and clinical stage data are given three separate areas in the NAACCR Data Exchange Record Layout.

• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.

• Codes (in addition to those published in the AJCC Cancer Staging Manual)

  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • 99 Unknown, not staged

• Note: See the AJCC Cancer Staging Manual, current edition for site-specific categories for the TNM elements and stage groups. See the STORE manual for specifications for codes and data entry rules.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#970

All data

st_css() #IMPORTANT!

  tnmclinstagegroup <- as.factor(trimws(d[,"tnmclinstagegroup"]))
  levels(tnmclinstagegroup)[levels(tnmclinstagegroup)=="88"] <- "Not_applicable.88"
  levels(tnmclinstagegroup)[levels(tnmclinstagegroup)=="99"] <- "Unknown.99"

    new.d <- data.frame(new.d, tnmclinstagegroup)
  new.d <- apply_labels(new.d, tnmclinstagegroup = "tnm_clin_stage_group")

temp.d <- data.frame (new.d.1, tnmclinstagegroup)
summarytools::view(dfSummary(new.d$tnmclinstagegroup, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnmclinstagegroup [labelled, factor]	tnm_clin_stage_group	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	352 ( 36.9% ) 22 ( 2.3% ) 179 ( 18.7% ) 126 ( 13.2% ) 45 ( 4.7% ) 78 ( 8.2% ) 153 ( 16.0% )		1212 (55.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	31 ( 54.4% ) 3 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 5.3% ) 5 ( 8.8% ) 15 ( 26.3% )		132 (69.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	37 ( 67.3% ) 6 ( 10.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 3.6% ) 8 ( 14.5% ) 2 ( 3.6% )		119 (68.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	32 ( 49.2% ) 4 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 6.2% ) 14 ( 21.5% ) 11 ( 16.9% )		172 (72.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	17 ( 12.8% ) 0 ( 0.0% ) 62 ( 46.6% ) 36 ( 27.1% ) 2 ( 1.5% ) 7 ( 5.3% ) 9 ( 6.8% )		41 (23.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	46 ( 16.1% ) 3 ( 1.1% ) 111 ( 38.9% ) 90 ( 31.6% ) 11 ( 3.9% ) 7 ( 2.5% ) 17 ( 6.0% )		5 (1.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	186 ( 53.3% ) 6 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 23 ( 6.6% ) 37 ( 10.6% ) 97 ( 27.8% )		738 (67.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tnm_clin_stage_group [factor]	1. 1 2. 2 3. 2A 4. 2B 5. 3 6. 4 7. Unknown.99	3 ( 27.3% ) 0 ( 0.0% ) 6 ( 54.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 18.2% )		5 (31.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM CLIN T

• Description: Detailed site-specific codes for the clinical tumor (T) as defined by the current AJCC edition.
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • Blank Information not available to code this item.
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1001

All data

st_css() #IMPORTANT!

  ajcctnmclint <- as.factor(trimws(d[,"ajcctnmclint"]))
  levels(ajcctnmclint)[levels(ajcctnmclint)=="88"] <- "Not_applicable.88"

    new.d <- data.frame(new.d, ajcctnmclint)
  new.d <- apply_labels(new.d, ajcctnmclint = "ajcc_tnm_clin_t")

temp.d <- data.frame (new.d.1, ajcctnmclint)
summarytools::view(dfSummary(new.d$ajcctnmclint, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmclint [labelled, factor]	ajcc_tnm_clin_t	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	1 ( 5.0% ) 11 ( 55.0% ) 2 ( 10.0% ) 4 ( 20.0% ) 1 ( 5.0% ) 1 ( 5.0% )		2147 (99.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	1 ( 5.3% ) 10 ( 52.6% ) 2 ( 10.5% ) 4 ( 21.1% ) 1 ( 5.3% ) 1 ( 5.3% )		155 (89.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_t [factor]	1. cT1a 2. cT1c 3. cT2 4. cT2a 5. cT3a 6. cTX	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM CLIN N

• Description: Detailed site-specific codes for the clinical nodes (N) as defined by the current AJCC edition.
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • Blank Information not available to code this item.
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1002

All data

st_css() #IMPORTANT!

  ajcctnmclinn <- as.factor(trimws(d[,"ajcctnmclinn"]))
  levels(ajcctnmclinn)[levels(ajcctnmclinn)=="88"] <- "Not_applicable.88"

    new.d <- data.frame(new.d, ajcctnmclinn)
  new.d <- apply_labels(new.d, ajcctnmclinn = "ajcc_tnm_clin_n")

temp.d <- data.frame (new.d.1, ajcctnmclinn)
summarytools::view(dfSummary(new.d$ajcctnmclinn, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmclinn [labelled, factor]	ajcc_tnm_clin_n	1. cN0 2. cN1 3. cNX	19 ( 90.5% ) 1 ( 4.8% ) 1 ( 4.8% )		2146 (99.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	18 ( 90.0% ) 1 ( 5.0% ) 1 ( 5.0% )		154 (88.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_n [factor]	1. cN0 2. cN1 3. cNX	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM CLIN M

• Description: Detailed site-specific codes for the clinical metastases (M) as defined by the current AJCC edition.
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • Blank Information not available to code this item.
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1003

All data

st_css() #IMPORTANT!

  ajcctnmclinm <- as.factor(trimws(d[,"ajcctnmclinm"]))
  levels(ajcctnmclinm)[levels(ajcctnmclinm)=="88"] <- "Not_applicable.88"

    new.d <- data.frame(new.d, ajcctnmclinm)
  new.d <- apply_labels(new.d, ajcctnmclinm = "ajcc_tnm_clin_m")

temp.d <- data.frame (new.d.1, ajcctnmclinm)
summarytools::view(dfSummary(new.d$ajcctnmclinm, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmclinm [labelled, factor]	ajcc_tnm_clin_m	1. cM0 2. cM1b 3. cM1c	19 ( 90.5% ) 1 ( 4.8% ) 1 ( 4.8% )		2146 (99.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	18 ( 90.0% ) 1 ( 5.0% ) 1 ( 5.0% )		154 (88.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_m [factor]	1. cM0 2. cM1b 3. cM1c	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM CLIN STAGE GROUP

• Description: Detailed site-specific codes for the clinical stage group as defined by the current AJCC edition.
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • 99 Unknown, not staged
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1004

All data

st_css() #IMPORTANT!

  ajcctnmclinstagegroup <- as.factor(trimws(d[,"ajcctnmclinstagegroup"]))
  levels(ajcctnmclinstagegroup)[levels(ajcctnmclinstagegroup)=="88"] <- "Not_applicable.88"
  levels(ajcctnmclinstagegroup)[levels(ajcctnmclinstagegroup)=="99"] <- "Unknown.99"

    new.d <- data.frame(new.d, ajcctnmclinstagegroup)
  new.d <- apply_labels(new.d, ajcctnmclinstagegroup = "ajcc_tnm_clin_stage_group")

temp.d <- data.frame (new.d.1, ajcctnmclinstagegroup)
summarytools::view(dfSummary(new.d$ajcctnmclinstagegroup, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmclinstagegroup [labelled, factor]	ajcc_tnm_clin_stage_group	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	4 ( 14.3% ) 2 ( 7.1% ) 3 ( 10.7% ) 5 ( 17.9% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 2 ( 7.1% ) 9 ( 32.1% )		2139 (98.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	3 ( 11.5% ) 2 ( 7.7% ) 3 ( 11.5% ) 5 ( 19.2% ) 1 ( 3.8% ) 1 ( 3.8% ) 1 ( 3.8% ) 2 ( 7.7% ) 8 ( 30.8% )		148 (85.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_clin_stage_group [factor]	1. 1 2. 2A 3. 2B 4. 2C 5. 3A 6. 3B 7. 3C 8. 4B 9. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM PATH T

• Description: Detailed site-specific codes for the pathologic tumor (T) as defined by the current AJCC edition.
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • Blank Information not available to code this item.
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1011

All data

st_css() #IMPORTANT!

  ajcctnmpatht <- as.factor(trimws(d[,"ajcctnmpatht"]))
  levels(ajcctnmpatht)[levels(ajcctnmpatht)=="88"] <- "Not_applicable.88"

    new.d <- data.frame(new.d, ajcctnmpatht)
  new.d <- apply_labels(new.d, ajcctnmpatht = "ajcc_tnm_path_t")

temp.d <- data.frame (new.d.1, ajcctnmpatht)
summarytools::view(dfSummary(new.d$ajcctnmpatht, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmpatht [labelled, factor]	ajcc_tnm_path_t	1. pT1b 2. pT2 3. pT3a	1 ( 20.0% ) 2 ( 40.0% ) 2 ( 40.0% )		2162 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	0 ( 0.0% ) 2 ( 50.0% ) 2 ( 50.0% )		170 (97.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_t [factor]	1. pT1b 2. pT2 3. pT3a	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM PATH N

• Description: Detailed site-specific codes for the pathologic nodes (N) as defined by the current AJCC edition.
  
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • Blank Information not available to code this item.
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1012

All data

st_css() #IMPORTANT!

  ajcctnmpathn <- as.factor(trimws(d[,"ajcctnmpathn"]))
  levels(ajcctnmpathn)[levels(ajcctnmpathn)=="88"] <- "Not_applicable.88"

    new.d <- data.frame(new.d, ajcctnmpathn)
  new.d <- apply_labels(new.d, ajcctnmpathn = "ajcc_tnm_path_n")

temp.d <- data.frame (new.d.1, ajcctnmpathn)
summarytools::view(dfSummary(new.d$ajcctnmpathn, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmpathn [labelled, factor]	ajcc_tnm_path_n	1. pN0 2. pNX	4 ( 80.0% ) 1 ( 20.0% )		2162 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	3 ( 75.0% ) 1 ( 25.0% )		170 (97.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	1 ( 100.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_n [factor]	1. pN0 2. pNX	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM PATH M

• Description: Detailed site-specific codes for the clinical path (M) as defined by the current AJCC edition.
  
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan trajcctnmpathneatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • Blank Information not available to code this item.
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1013

All data

st_css() #IMPORTANT!

  ajcctnmpathm <- as.factor(trimws(d[,"ajcctnmpathm"]))
  levels(ajcctnmpathm)[levels(ajcctnmpathm)=="88"] <- "Not_applicable.88"

    new.d <- data.frame(new.d, ajcctnmpathm)
  new.d <- apply_labels(new.d, ajcctnmpathm = "ajcc_tnm_path_m")

temp.d <- data.frame (new.d.1, ajcctnmpathm)
summarytools::view(dfSummary(new.d$ajcctnmpathm, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmpathm [labelled, factor]	ajcc_tnm_path_m	1. cM0	5 ( 100.0% )		2162 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	4 ( 100.0% )		170 (97.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	1 ( 100.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_m [factor]	1. cM0	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

AJCC TNM PATH STAGE GROUP

• Description: Detailed site-specific codes for the pathologic stage group as defined by the current AJCC edition.
• Rationale: CoC requires that AJCC TNM staging be used in its approved cancer programs. AJCC developed its staging system for evaluating trends in the treatment and control of cancer. This staging is used by physicians to estimate prognosis, to plan treatment, to evaluate new types of therapy, to analyze outcome, to design follow-up strategies, and to assess early detection results.
• Codes (in addition to those published in the AJCC Cancer Staging Manual)
  • 88 Not applicable, no code assigned for this case in the current AJCC Staging Manual.
  • 99 Unknown, not staged
• Note: See the AJCC Cancer Staging Manual, 8th edition for site-specific categories for the TNM elements and stage groups. See the CURRENT STORE manual for specifications for codes and data entry rules.
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1014

All data

st_css() #IMPORTANT!

  ajcctnmpathstagegroup <- as.factor(trimws(d[,"ajcctnmpathstagegroup"]))
  levels(ajcctnmpathstagegroup)[levels(ajcctnmpathstagegroup)=="88"] <- "Not_applicable.88"
  levels(ajcctnmpathstagegroup)[levels(ajcctnmpathstagegroup)=="99"] <- "Unknown.99"

    new.d <- data.frame(new.d, ajcctnmpathstagegroup)
  new.d <- apply_labels(new.d, ajcctnmpathstagegroup = "ajcc_tnm_path_stage_group")

temp.d <- data.frame (new.d.1, ajcctnmpathstagegroup)
summarytools::view(dfSummary(new.d$ajcctnmpathstagegroup, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcctnmpathstagegroup [labelled, factor]	ajcc_tnm_path_stage_group	1. 1B 2. 3B 3. 3C 4. Unknown.99	1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 25 ( 89.3% )		2139 (98.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	0 ( 0.0% ) 1 ( 3.8% ) 1 ( 3.8% ) 24 ( 92.3% )		148 (85.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	ajcc_tnm_path_stage_group [factor]	1. 1B 2. 3B 3. 3C 4. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

TUMOR MARKER 2

• Description: Records prognostic indicators for specific sites or histologies. CoC offered these items for optional use for cases diagnosed 1996 and forward. See the CoC ROADS Manual, 1998 Supplement, for a list of specific sites and histologies.

• For SEER requirements for the specific sites, histologies, and diagnosis years for which this item is coded, see the 1998 SEER Program Code Manual.

• Codes

  • 0 None done (SX)
  • 1 Positive/elevated
  • 2 Negative/normal; within normal limits (S0)
  • 3 Borderline; undetermined whether positive/elevated or negative/normal

• Three-tiered system:

  • 4 Range 1 (S1)
  • 5 Range 2 (S2)
  • 6 Range 3 (S3)
  • 8 Ordered, but results not in chart
  • 9 Not applicable

• For sites for which Tumor Marker 2 is not collected:

  • 9 Not applicable

• Note: As of January 1, 2003, this data item is no longer required or recommended by CoC. However, the item was collected in the past and it is recommended that historic data be retained.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1160

All data

st_css() #IMPORTANT!

  tumormarker2 <- as.factor(trimws(d[,"tumormarker2"]))

    new.d <- data.frame(new.d, tumormarker2)
  new.d <- apply_labels(new.d, tumormarker2 = "tumor_marker2")

temp.d <- data.frame (new.d.1, tumormarker2)
summarytools::view(dfSummary(new.d$tumormarker2, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	tumormarker2 [labelled, factor]	tumor_marker2	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE SURGERY

• Description: Date the first surgery of the type described under Surgery of Primary Site, Scope of Regional Lymph Node Surgery, or Surgery of Other Regional Site(s), Distant Site(s) or Distant Lymph Nodes was performed. See also RX Summ–Surg Prim Site [1290], RX Summ–Scope Reg LN Sur [1292], and RX Summ–Surg Oth Reg/Dis [1294]. See Chapter X for date format. Formerly RX Date–Surgery.

• Rationale: The dates on which different treatment modalities were started are used to evaluate whether the treatments were part of first-course therapy and to reconstruct the sequence of first-course treatment modes.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1200

All data

st_css() #IMPORTANT!

  rxdatesurgery <- as.factor(d[,"rxdatesurgery"])
  
    new.d <- data.frame(new.d, rxdatesurgery)
    new.d <- apply_labels(new.d, rxdatesurgery = "rx_date_surgery")
    #summary(new.d$rxdatesurgery)
temp.d <- data.frame (new.d.1, rxdatesurgery)
summarytools::view(dfSummary(new.d$rxdatesurgery, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatesurgery [labelled, factor]	rx_date_surgery	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 5 ( 0.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 3 ( 0.3% ) 7 ( 0.7% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 5 ( 0.5% ) 2 ( 0.2% ) 6 ( 0.6% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 11 ( 1.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 3 ( 0.3% ) 1 ( 0.1% ) 923 ( 90.0% )		1142 (52.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 4.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 91 ( 86.7% )		84 (44.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 45 ( 93.8% )		126 (72.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 128 ( 88.9% )		93 (39.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 3.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 78 ( 91.8% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 3 ( 1.6% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 160 ( 87.9% )		108 (37.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 3 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.4% ) 1 ( 0.2% ) 0 ( 0.0% ) 3 ( 0.7% ) 1 ( 0.2% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 2 ( 0.4% ) 2 ( 0.4% ) 1 ( 0.2% ) 421 ( 92.7% )		633 (58.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_surgery [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150522 43. 20150527 44. 20150528 45. 20150599 46. 201506  · 47. 20150601 48. 20150603 49. 20150605 50. 20150610 [ 417 others ]	1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		9 (56.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE RADIATION

• Description: Records the date on which radiation therapy began at any facility that is part of the first course of treatment. See Chapter X for date format. Use RX DATE RADIATION FLAG [1211] if there is no appropriate or known date for this item. Formerly RX Date–Radiation

• Rationale: The dates on which different treatment modalities were started are used to evaluate whether the treatments were part of first-course therapy and to reconstruct the sequence of first-course treatment modes.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1210

All data

st_css() #IMPORTANT!

  rxdateradiation <- as.factor(d[,"rxdateradiation"])
  
    new.d <- data.frame(new.d, rxdateradiation)
    new.d <- apply_labels(new.d, rxdateradiation = "rx_date_radiation")
    #summary(new.d$rxdateradiation)
temp.d <- data.frame (new.d.1, rxdateradiation)
summarytools::view(dfSummary(new.d$rxdateradiation, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdateradiation [labelled, factor]	rx_date_radiation	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 3 ( 0.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.4% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 6 ( 0.7% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 6 ( 0.7% ) 1 ( 0.1% ) 5 ( 0.6% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 4 ( 0.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 4 ( 0.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.4% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 747 ( 89.4% )		1331 (61.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 6.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 4.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 40 ( 85.1% )		142 (75.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 72 ( 92.3% )		96 (55.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 3.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 3.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 53 ( 89.8% )		178 (75.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 3.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 57 ( 95.0% )		114 (65.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 89 ( 91.8% )		193 (66.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 2 ( 0.4% ) 0 ( 0.0% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 3 ( 0.6% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.2% ) 5 ( 1.0% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 3 ( 0.6% ) 1 ( 0.2% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 2 ( 0.4% ) 435 ( 88.8% )		597 (54.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_radiation [factor]	1. 20130599 2. 20130699 3. 20140799 4. 20150199 5. 20150205 6. 20150224 7. 201503  · 8. 20150317 9. 20150323 10. 20150326 11. 201504  · 12. 20150401 13. 20150407 14. 20150409 15. 20150420 16. 20150423 17. 20150428 18. 20150429 19. 20150499 20. 201505  · 21. 20150504 22. 20150506 23. 20150509 24. 20150511 25. 20150514 26. 20150520 27. 20150521 28. 20150526 29. 20150527 30. 201506  · 31. 20150601 32. 20150602 33. 20150606 34. 20150608 35. 20150609 36. 20150615 37. 20150617 38. 20150618 39. 20150622 40. 20150625 41. 20150699 42. 201507  · 43. 20150701 44. 20150706 45. 20150708 46. 20150713 47. 20150714 48. 20150715 49. 20150716 50. 20150720 [ 381 others ]	1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% )		11 (68.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE CHEMO

• Description: Date of initiation of chemotherapy that is part of the first course of treatment. See also RX Summ–Chemo [1390]. See Chapter X for date format. Formerly RX Date–Chemo.

• Rationale: The dates on which different treatment modalities were started are used to evaluate whether the treatments were part of first-course therapy and to reconstruct the sequence of first-course treatment modes. Note: CoC discontinued support of this item from 2003 through 2009.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1220

All data

st_css() #IMPORTANT!

  rxdatechemo <- as.factor(d[,"rxdatechemo"])
  
    new.d <- data.frame(new.d, rxdatechemo)
    new.d <- apply_labels(new.d, rxdatechemo = "rx_date_chemo")
    #summary(new.d$rxdatechemo)
temp.d <- data.frame (new.d.1, rxdatechemo)
summarytools::view(dfSummary(new.d$rxdatechemo, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatechemo [labelled, factor]	rx_date_chemo	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 4 ( 13.8% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% ) 1 ( 3.4% )		2138 (98.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		188 (99.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 75.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		170 (97.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		230 (97.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		289 (99.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% )		1071 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_chemo [factor]	1. 201503  · 2. 20150423 3. 20150515 4. 201509  · 5. 20151022 6. 20151202 7. 20160120 8. 20160223 9. 201604  · 10. 201606  · 11. 20160608 12. 20160720 13. 201608  · 14. 201610  · 15. 20161021 16. 20161111 17. 20161122 18. 20161130 19. 201612  · 20. 201701  · 21. 20170119 22. 201702  · 23. 20170202 24. 20170516 25. 20170601 26. 20180403	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE HORMONE

• Description: Date of initiation for hormone therapy that is part of the first course of treatment. See also RX Summ–Hormone [1400]. See Chapter X for date format. Formerly RX Date–Hormone.

• Rationale: The dates on which different treatment modalities were started are used to evaluate whether the treatments were part of first-course therapy and to reconstruct the sequence of first-course treatment modes. Note: CoC discontinued support of this item from 2003 through 2009.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1230

All data

st_css() #IMPORTANT!

  rxdatehormone <- as.factor(d[,"rxdatehormone"])
  
    new.d <- data.frame(new.d, rxdatehormone)
    new.d <- apply_labels(new.d, rxdatehormone = "rx_date_hormone")
    #summary(new.d$rxdatehormone)
temp.d <- data.frame (new.d.1, rxdatehormone)
summarytools::view(dfSummary(new.d$rxdatehormone, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatehormone [labelled, factor]	rx_date_hormone	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 5 ( 1.1% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 6 ( 1.3% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 4 ( 0.9% ) 1 ( 0.2% ) 399 ( 85.1% )		1698 (78.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 32 ( 86.5% )		152 (80.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 41 ( 89.1% )		128 (73.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 7.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 7.0% ) 0 ( 0.0% ) 34 ( 79.1% )		194 (81.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 39 ( 90.7% )		131 (75.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 62 ( 80.5% )		213 (73.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.9% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.9% ) 1 ( 0.5% ) 2 ( 0.9% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 191 ( 86.0% )		865 (79.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_hormone [factor]	1. 20130499 2. 201501  · 3. 20150116 4. 20150126 5. 201502  · 6. 20150210 7. 20150211 8. 20150217 9. 201503  · 10. 20150306 11. 20150326 12. 20150399 13. 201504  · 14. 20150401 15. 20150410 16. 20150415 17. 20150428 18. 20150499 19. 201505  · 20. 20150504 21. 20150505 22. 20150507 23. 20150509 24. 20150514 25. 20150519 26. 20150521 27. 20150526 28. 20150528 29. 201506  · 30. 20150601 31. 20150602 32. 20150604 33. 20150608 34. 20150611 35. 20150612 36. 20150615 37. 20150616 38. 20150618 39. 20150619 40. 20150623 41. 20150625 42. 20150626 43. 20150627 44. 20150699 45. 20150702 46. 20150709 47. 20150727 48. 20150799 49. 201508  · 50. 20150801 [ 235 others ]	1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		15 (93.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE BRM

• Description: Date of initiation for immunotherapy (a.k.a. biological response modifier) that is part of the first course of treatment. See also RX Summ–BRM [1410]. See Chapter X for date format. Formerly RX Date–BRM.

• Rationale: The dates on which different treatment modalities were started are used to evaluate whether the treatments were part of first course of therapy and to reconstruct the sequence of first-course treatment modes. Note: CoC discontinued support of this item from 2003 through 2009.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1240

All data

st_css() #IMPORTANT!

  rxdatebrm <- as.factor(d[,"rxdatebrm"])
  
    new.d <- data.frame(new.d, rxdatebrm)
    new.d <- apply_labels(new.d, rxdatebrm = "rx_date_brm")
    #summary(new.d$rxdatebrm)
temp.d <- data.frame (new.d.1, rxdatebrm)
summarytools::view(dfSummary(new.d$rxdatebrm, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatebrm [labelled, factor]	rx_date_brm	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% )		2162 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% )		236 (99.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	1 ( 25.0% ) 1 ( 25.0% ) 1 ( 25.0% ) 1 ( 25.0% ) 0 ( 0.0% )		1083 (99.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_brm [factor]	1. 20160308 2. 20160921 3. 20170130 4. 20170215 5. 201705  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE OTHER

• Description: Date of initiation for other treatment that is part of the first course of treatment at any facility. See RX Summ–Other [1420]. See Chapter X for date format. Formerly RX Date–Other.

• Rationale: The dates on which different treatment modalities were started are used to evaluate whether the treatments were part of first-course therapy and to reconstruct the sequence of first-course treatment modes.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1250

All data

st_css() #IMPORTANT!

  rxdateother <- as.factor(d[,"rxdateother"])
  
    new.d <- data.frame(new.d, rxdateother)
    new.d <- apply_labels(new.d, rxdateother = "rx_date_other")
    #summary(new.d$rxdateother)
temp.d <- data.frame (new.d.1, rxdateother)
summarytools::view(dfSummary(new.d$rxdateother, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdateother [labelled, factor]	rx_date_other	1. 20150911 2. 201605  · 3. 20160711	1 ( 33.3% ) 1 ( 33.3% ) 1 ( 33.3% )		2164 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% )		236 (99.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	1 ( 50.0% ) 0 ( 0.0% ) 1 ( 50.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_other [factor]	1. 20150911 2. 201605  · 3. 20160711	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DATE INITIAL RX SEER

• Description: Date of initiation of the first course therapy for the tumor being reported, using the SEER definition of first course. See also Date 1st Crs RX CoC [1270]. See Chapter V, Unresolved Issues, for further discussion of the difference between SEER and CoC items. See Chapter X for date format. Use Date Initial RX SEER Flag [1261] if there is no appropriate or known date for this item. Formerly Date of Initial RX–SEER.

• Clarification of NPCR Required Status: Central registries funded by NPCR are required to collect either Date Initial RX SEER [1260] or Date 1st Crs RX CoC [1270].

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1260

All data

st_css() #IMPORTANT!

  dateinitialrxseer <- as.factor(d[,"dateinitialrxseer"])
  
    new.d <- data.frame(new.d, dateinitialrxseer)
    new.d <- apply_labels(new.d, dateinitialrxseer = "date_initial_rx_seer")
    #summary(new.d$dateinitialrxseer)
temp.d <- data.frame (new.d.1, dateinitialrxseer)
summarytools::view(dfSummary(new.d$dateinitialrxseer, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	dateinitialrxseer [labelled, factor]	date_initial_rx_seer	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 4 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 8 ( 0.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 5 ( 0.3% ) 4 ( 0.2% ) 13 ( 0.7% ) 6 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.2% ) 2 ( 0.1% ) 3 ( 0.2% ) 2 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 8 ( 0.4% ) 1 ( 0.1% ) 4 ( 0.2% ) 1727 ( 94.1% )		332 (15.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 3.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 145 ( 93.5% )		34 (18.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 125 ( 96.2% )		44 (25.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 2 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 196 ( 93.8% )		28 (11.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.8% ) 133 ( 94.3% )		33 (19.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 2 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 3 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 4 ( 1.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 241 ( 91.3% )		26 (9.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 5 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 4 ( 0.4% ) 1 ( 0.1% ) 0 ( 0.0% ) 886 ( 95.8% )		162 (14.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_initial_rx_seer [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20130499 5. 20130699 6. 20131199 7. 20140299 8. 20140599 9. 20141199 10. 2015  · 11. 201501  · 12. 20150116 13. 20150126 14. 20150199 15. 201502  · 16. 20150205 17. 20150210 18. 20150211 19. 20150212 20. 20150217 21. 20150219 22. 20150223 23. 20150224 24. 20150226 25. 201503  · 26. 20150306 27. 20150310 28. 20150316 29. 20150317 30. 20150323 31. 20150326 32. 20150399 33. 201504  · 34. 20150401 35. 20150402 36. 20150406 37. 20150407 38. 20150409 39. 20150410 40. 20150413 41. 20150414 42. 20150415 43. 20150416 44. 20150420 45. 20150421 46. 20150423 47. 20150427 48. 20150428 49. 20150429 50. 20150499 [ 552 others ]	1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% )		5 (31.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE DX/STG PROC

• Description: Records the date on which the surgical diagnostic and/or staging procedure was performed. See Surgical and Diagnostic Staging Procedure [1350]. See Chapter X for date format. Formerly RX Date–DX/Stg Proc.

• Note: This is a CoC item and for tumors diagnosed from January 1, 1996, through December 31, 2002, this may have been the date on which diagnostic, staging, and palliative procedures were performed. Beginning with tumors diagnosed on or after January 1, 2003, palliative procedures are collected in RX Summ–Palliative Proc [3270] and RX Hosp–Palliative Proc [3280].

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1280

All data

st_css() #IMPORTANT!

  rxdatedxstgproc <- as.factor(d[,"rxdatedxstgproc"])
  
    new.d <- data.frame(new.d, rxdatedxstgproc)
    new.d <- apply_labels(new.d, rxdatedxstgproc = "rx_date_dxstg_proc")
    #summary(new.d$rxdatedxstgproc)
temp.d <- data.frame (new.d.1, rxdatedxstgproc)
summarytools::view(dfSummary(new.d$rxdatedxstgproc, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatedxstgproc [labelled, factor]	rx_date_dxstg_proc	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 [ 162 others ]	1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 223 ( 78.8% )		1884 (86.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 51. 20150707 52. 20150709 53. 20150710 54. 20150715 55. 20150717 56. 20150721 57. 20150724 58. 20150727 59. 20150730 60. 20150803 61. 20150805 62. 20150810 63. 20150813 64. 20150818 65. 20150824 66. 20150827 67. 20150908 68. 20150909 69. 20150910 70. 20150911 71. 20150917 72. 20150922 73. 20150924 74. 20150930 75. 20151001 76. 20151007 77. 20151019 78. 20151021 79. 20151023 80. 20151030 81. 20151103 82. 20151104 83. 20151105 84. 20151110 85. 20151113 86. 20151117 87. 20151130 88. 20151201 89. 20151202 90. 20151204 91. 20151218 92. 20151228 93. 20151229 94. 20151230 95. 2016  · 96. 201601  · 97. 20160104 98. 20160106 99. 20160107 100. 20160115 101. 20160120 102. 20160125 103. 20160126 104. 20160128 105. 20160205 106. 20160208 107. 20160210 108. 20160215 109. 20160224 110. 20160225 111. 20160226 112. 201603  · 113. 20160310 114. 20160311 115. 20160315 116. 20160318 117. 20160321 118. 20160322 119. 20160324 120. 20160329 121. 20160330 122. 201604  · 123. 20160401 124. 20160405 125. 20160411 126. 20160412 127. 20160415 128. 20160418 129. 20160419 130. 20160425 131. 20160426 132. 20160429 133. 20160504 134. 20160505 135. 20160509 136. 20160510 137. 20160512 138. 20160516 139. 20160518 140. 20160519 141. 20160520 142. 20160526 143. 20160531 144. 201606  · 145. 20160602 146. 20160607 147. 20160608 148. 20160610 149. 20160613 150. 20160615 151. 20160616 152. 20160617 153. 20160621 154. 20160622 155. 20160630 156. 20160701 157. 20160705 158. 20160711 159. 20160712 160. 20160714 161. 20160718 162. 20160721 163. 20160726 164. 20160728 165. 20160801 166. 20160802 167. 20160803 168. 20160804 169. 20160805 170. 20160809 171. 20160812 172. 20160817 173. 20160824 174. 20160825 175. 20160831 176. 20160906 177. 20160908 178. 20160909 179. 20160912 180. 20160913 181. 20160916 182. 20160920 183. 20160922 184. 20160923 185. 20160926 186. 20161007 187. 20161010 188. 20161012 189. 20161013 190. 20161017 191. 20161019 192. 20161020 193. 20161021 194. 20161031 195. 20161108 196. 20161109 197. 20161115 198. 20161117 199. 20161122 200. 20161123 201. 20161128 202. 20161130 203. 20161205 204. 20161207 205. 20161208 206. 20161212 207. 20161213 208. 20161214 209. 20161216 210. 20161219 211. 20161221 212. 20161230	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 51. 20150707 52. 20150709 53. 20150710 54. 20150715 55. 20150717 56. 20150721 57. 20150724 58. 20150727 59. 20150730 60. 20150803 61. 20150805 62. 20150810 63. 20150813 64. 20150818 65. 20150824 66. 20150827 67. 20150908 68. 20150909 69. 20150910 70. 20150911 71. 20150917 72. 20150922 73. 20150924 74. 20150930 75. 20151001 76. 20151007 77. 20151019 78. 20151021 79. 20151023 80. 20151030 81. 20151103 82. 20151104 83. 20151105 84. 20151110 85. 20151113 86. 20151117 87. 20151130 88. 20151201 89. 20151202 90. 20151204 91. 20151218 92. 20151228 93. 20151229 94. 20151230 95. 2016  · 96. 201601  · 97. 20160104 98. 20160106 99. 20160107 100. 20160115 101. 20160120 102. 20160125 103. 20160126 104. 20160128 105. 20160205 106. 20160208 107. 20160210 108. 20160215 109. 20160224 110. 20160225 111. 20160226 112. 201603  · 113. 20160310 114. 20160311 115. 20160315 116. 20160318 117. 20160321 118. 20160322 119. 20160324 120. 20160329 121. 20160330 122. 201604  · 123. 20160401 124. 20160405 125. 20160411 126. 20160412 127. 20160415 128. 20160418 129. 20160419 130. 20160425 131. 20160426 132. 20160429 133. 20160504 134. 20160505 135. 20160509 136. 20160510 137. 20160512 138. 20160516 139. 20160518 140. 20160519 141. 20160520 142. 20160526 143. 20160531 144. 201606  · 145. 20160602 146. 20160607 147. 20160608 148. 20160610 149. 20160613 150. 20160615 151. 20160616 152. 20160617 153. 20160621 154. 20160622 155. 20160630 156. 20160701 157. 20160705 158. 20160711 159. 20160712 160. 20160714 161. 20160718 162. 20160721 163. 20160726 164. 20160728 165. 20160801 166. 20160802 167. 20160803 168. 20160804 169. 20160805 170. 20160809 171. 20160812 172. 20160817 173. 20160824 174. 20160825 175. 20160831 176. 20160906 177. 20160908 178. 20160909 179. 20160912 180. 20160913 181. 20160916 182. 20160920 183. 20160922 184. 20160923 185. 20160926 186. 20161007 187. 20161010 188. 20161012 189. 20161013 190. 20161017 191. 20161019 192. 20161020 193. 20161021 194. 20161031 195. 20161108 196. 20161109 197. 20161115 198. 20161117 199. 20161122 200. 20161123 201. 20161128 202. 20161130 203. 20161205 204. 20161207 205. 20161208 206. 20161212 207. 20161213 208. 20161214 209. 20161216 210. 20161219 211. 20161221 212. 20161230	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 51. 20150707 52. 20150709 53. 20150710 54. 20150715 55. 20150717 56. 20150721 57. 20150724 58. 20150727 59. 20150730 60. 20150803 61. 20150805 62. 20150810 63. 20150813 64. 20150818 65. 20150824 66. 20150827 67. 20150908 68. 20150909 69. 20150910 70. 20150911 71. 20150917 72. 20150922 73. 20150924 74. 20150930 75. 20151001 76. 20151007 77. 20151019 78. 20151021 79. 20151023 80. 20151030 81. 20151103 82. 20151104 83. 20151105 84. 20151110 85. 20151113 86. 20151117 87. 20151130 88. 20151201 89. 20151202 90. 20151204 91. 20151218 92. 20151228 93. 20151229 94. 20151230 95. 2016  · 96. 201601  · 97. 20160104 98. 20160106 99. 20160107 100. 20160115 101. 20160120 102. 20160125 103. 20160126 104. 20160128 105. 20160205 106. 20160208 107. 20160210 108. 20160215 109. 20160224 110. 20160225 111. 20160226 112. 201603  · 113. 20160310 114. 20160311 115. 20160315 116. 20160318 117. 20160321 118. 20160322 119. 20160324 120. 20160329 121. 20160330 122. 201604  · 123. 20160401 124. 20160405 125. 20160411 126. 20160412 127. 20160415 128. 20160418 129. 20160419 130. 20160425 131. 20160426 132. 20160429 133. 20160504 134. 20160505 135. 20160509 136. 20160510 137. 20160512 138. 20160516 139. 20160518 140. 20160519 141. 20160520 142. 20160526 143. 20160531 144. 201606  · 145. 20160602 146. 20160607 147. 20160608 148. 20160610 149. 20160613 150. 20160615 151. 20160616 152. 20160617 153. 20160621 154. 20160622 155. 20160630 156. 20160701 157. 20160705 158. 20160711 159. 20160712 160. 20160714 161. 20160718 162. 20160721 163. 20160726 164. 20160728 165. 20160801 166. 20160802 167. 20160803 168. 20160804 169. 20160805 170. 20160809 171. 20160812 172. 20160817 173. 20160824 174. 20160825 175. 20160831 176. 20160906 177. 20160908 178. 20160909 179. 20160912 180. 20160913 181. 20160916 182. 20160920 183. 20160922 184. 20160923 185. 20160926 186. 20161007 187. 20161010 188. 20161012 189. 20161013 190. 20161017 191. 20161019 192. 20161020 193. 20161021 194. 20161031 195. 20161108 196. 20161109 197. 20161115 198. 20161117 199. 20161122 200. 20161123 201. 20161128 202. 20161130 203. 20161205 204. 20161207 205. 20161208 206. 20161212 207. 20161213 208. 20161214 209. 20161216 210. 20161219 211. 20161221 212. 20161230	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 51. 20150707 52. 20150709 53. 20150710 54. 20150715 55. 20150717 56. 20150721 57. 20150724 58. 20150727 59. 20150730 60. 20150803 61. 20150805 62. 20150810 63. 20150813 64. 20150818 65. 20150824 66. 20150827 67. 20150908 68. 20150909 69. 20150910 70. 20150911 71. 20150917 72. 20150922 73. 20150924 74. 20150930 75. 20151001 76. 20151007 77. 20151019 78. 20151021 79. 20151023 80. 20151030 81. 20151103 82. 20151104 83. 20151105 84. 20151110 85. 20151113 86. 20151117 87. 20151130 88. 20151201 89. 20151202 90. 20151204 91. 20151218 92. 20151228 93. 20151229 94. 20151230 95. 2016  · 96. 201601  · 97. 20160104 98. 20160106 99. 20160107 100. 20160115 101. 20160120 102. 20160125 103. 20160126 104. 20160128 105. 20160205 106. 20160208 107. 20160210 108. 20160215 109. 20160224 110. 20160225 111. 20160226 112. 201603  · 113. 20160310 114. 20160311 115. 20160315 116. 20160318 117. 20160321 118. 20160322 119. 20160324 120. 20160329 121. 20160330 122. 201604  · 123. 20160401 124. 20160405 125. 20160411 126. 20160412 127. 20160415 128. 20160418 129. 20160419 130. 20160425 131. 20160426 132. 20160429 133. 20160504 134. 20160505 135. 20160509 136. 20160510 137. 20160512 138. 20160516 139. 20160518 140. 20160519 141. 20160520 142. 20160526 143. 20160531 144. 201606  · 145. 20160602 146. 20160607 147. 20160608 148. 20160610 149. 20160613 150. 20160615 151. 20160616 152. 20160617 153. 20160621 154. 20160622 155. 20160630 156. 20160701 157. 20160705 158. 20160711 159. 20160712 160. 20160714 161. 20160718 162. 20160721 163. 20160726 164. 20160728 165. 20160801 166. 20160802 167. 20160803 168. 20160804 169. 20160805 170. 20160809 171. 20160812 172. 20160817 173. 20160824 174. 20160825 175. 20160831 176. 20160906 177. 20160908 178. 20160909 179. 20160912 180. 20160913 181. 20160916 182. 20160920 183. 20160922 184. 20160923 185. 20160926 186. 20161007 187. 20161010 188. 20161012 189. 20161013 190. 20161017 191. 20161019 192. 20161020 193. 20161021 194. 20161031 195. 20161108 196. 20161109 197. 20161115 198. 20161117 199. 20161122 200. 20161123 201. 20161128 202. 20161130 203. 20161205 204. 20161207 205. 20161208 206. 20161212 207. 20161213 208. 20161214 209. 20161216 210. 20161219 211. 20161221 212. 20161230	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 [ 162 others ]	1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.7% ) 223 ( 78.8% )		7 (2.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 51. 20150707 52. 20150709 53. 20150710 54. 20150715 55. 20150717 56. 20150721 57. 20150724 58. 20150727 59. 20150730 60. 20150803 61. 20150805 62. 20150810 63. 20150813 64. 20150818 65. 20150824 66. 20150827 67. 20150908 68. 20150909 69. 20150910 70. 20150911 71. 20150917 72. 20150922 73. 20150924 74. 20150930 75. 20151001 76. 20151007 77. 20151019 78. 20151021 79. 20151023 80. 20151030 81. 20151103 82. 20151104 83. 20151105 84. 20151110 85. 20151113 86. 20151117 87. 20151130 88. 20151201 89. 20151202 90. 20151204 91. 20151218 92. 20151228 93. 20151229 94. 20151230 95. 2016  · 96. 201601  · 97. 20160104 98. 20160106 99. 20160107 100. 20160115 101. 20160120 102. 20160125 103. 20160126 104. 20160128 105. 20160205 106. 20160208 107. 20160210 108. 20160215 109. 20160224 110. 20160225 111. 20160226 112. 201603  · 113. 20160310 114. 20160311 115. 20160315 116. 20160318 117. 20160321 118. 20160322 119. 20160324 120. 20160329 121. 20160330 122. 201604  · 123. 20160401 124. 20160405 125. 20160411 126. 20160412 127. 20160415 128. 20160418 129. 20160419 130. 20160425 131. 20160426 132. 20160429 133. 20160504 134. 20160505 135. 20160509 136. 20160510 137. 20160512 138. 20160516 139. 20160518 140. 20160519 141. 20160520 142. 20160526 143. 20160531 144. 201606  · 145. 20160602 146. 20160607 147. 20160608 148. 20160610 149. 20160613 150. 20160615 151. 20160616 152. 20160617 153. 20160621 154. 20160622 155. 20160630 156. 20160701 157. 20160705 158. 20160711 159. 20160712 160. 20160714 161. 20160718 162. 20160721 163. 20160726 164. 20160728 165. 20160801 166. 20160802 167. 20160803 168. 20160804 169. 20160805 170. 20160809 171. 20160812 172. 20160817 173. 20160824 174. 20160825 175. 20160831 176. 20160906 177. 20160908 178. 20160909 179. 20160912 180. 20160913 181. 20160916 182. 20160920 183. 20160922 184. 20160923 185. 20160926 186. 20161007 187. 20161010 188. 20161012 189. 20161013 190. 20161017 191. 20161019 192. 20161020 193. 20161021 194. 20161031 195. 20161108 196. 20161109 197. 20161115 198. 20161117 199. 20161122 200. 20161123 201. 20161128 202. 20161130 203. 20161205 204. 20161207 205. 20161208 206. 20161212 207. 20161213 208. 20161214 209. 20161216 210. 20161219 211. 20161221 212. 20161230	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_dxstg_proc [factor]	1. 2015  · 2. 20150101 3. 20150106 4. 20150112 5. 20150114 6. 20150115 7. 20150116 8. 20150119 9. 20150202 10. 20150210 11. 20150212 12. 20150216 13. 20150218 14. 20150220 15. 201503  · 16. 20150302 17. 20150303 18. 20150304 19. 20150305 20. 20150310 21. 20150311 22. 20150323 23. 20150326 24. 20150402 25. 20150406 26. 20150407 27. 20150413 28. 20150416 29. 20150417 30. 20150423 31. 20150424 32. 20150511 33. 20150513 34. 20150515 35. 20150519 36. 20150520 37. 20150521 38. 20150526 39. 20150528 40. 20150603 41. 20150604 42. 20150609 43. 20150616 44. 20150617 45. 20150619 46. 20150622 47. 20150623 48. 20150624 49. 20150625 50. 20150629 51. 20150707 52. 20150709 53. 20150710 54. 20150715 55. 20150717 56. 20150721 57. 20150724 58. 20150727 59. 20150730 60. 20150803 61. 20150805 62. 20150810 63. 20150813 64. 20150818 65. 20150824 66. 20150827 67. 20150908 68. 20150909 69. 20150910 70. 20150911 71. 20150917 72. 20150922 73. 20150924 74. 20150930 75. 20151001 76. 20151007 77. 20151019 78. 20151021 79. 20151023 80. 20151030 81. 20151103 82. 20151104 83. 20151105 84. 20151110 85. 20151113 86. 20151117 87. 20151130 88. 20151201 89. 20151202 90. 20151204 91. 20151218 92. 20151228 93. 20151229 94. 20151230 95. 2016  · 96. 201601  · 97. 20160104 98. 20160106 99. 20160107 100. 20160115 101. 20160120 102. 20160125 103. 20160126 104. 20160128 105. 20160205 106. 20160208 107. 20160210 108. 20160215 109. 20160224 110. 20160225 111. 20160226 112. 201603  · 113. 20160310 114. 20160311 115. 20160315 116. 20160318 117. 20160321 118. 20160322 119. 20160324 120. 20160329 121. 20160330 122. 201604  · 123. 20160401 124. 20160405 125. 20160411 126. 20160412 127. 20160415 128. 20160418 129. 20160419 130. 20160425 131. 20160426 132. 20160429 133. 20160504 134. 20160505 135. 20160509 136. 20160510 137. 20160512 138. 20160516 139. 20160518 140. 20160519 141. 20160520 142. 20160526 143. 20160531 144. 201606  · 145. 20160602 146. 20160607 147. 20160608 148. 20160610 149. 20160613 150. 20160615 151. 20160616 152. 20160617 153. 20160621 154. 20160622 155. 20160630 156. 20160701 157. 20160705 158. 20160711 159. 20160712 160. 20160714 161. 20160718 162. 20160721 163. 20160726 164. 20160728 165. 20160801 166. 20160802 167. 20160803 168. 20160804 169. 20160805 170. 20160809 171. 20160812 172. 20160817 173. 20160824 174. 20160825 175. 20160831 176. 20160906 177. 20160908 178. 20160909 179. 20160912 180. 20160913 181. 20160916 182. 20160920 183. 20160922 184. 20160923 185. 20160926 186. 20161007 187. 20161010 188. 20161012 189. 20161013 190. 20161017 191. 20161019 192. 20161020 193. 20161021 194. 20161031 195. 20161108 196. 20161109 197. 20161115 198. 20161117 199. 20161122 200. 20161123 201. 20161128 202. 20161130 203. 20161205 204. 20161207 205. 20161208 206. 20161212 207. 20161213 208. 20161214 209. 20161216 210. 20161219 211. 20161221 212. 20161230	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

# RX SUMM–TREATMENT STATUS {.tabset} - Description: This data item is a summary of the status for all treatment modalities. It is used in conjunction with Date Initial RX SEER [1260] and/or Date 1st Crs RX CoC [1270] and each modality of treatment with their respective date field to document whether treatment was given or not given, whether it is unknown if treatment was given, or whether treatment was given on an unknown date. Also indicates active surveillance (watchful waiting). This data item is effective for January 2010+ diagnoses.

• Rationale: This field will document active surveillance (watchful waiting) and eliminate searching each treatment modality to determine whether treatment was given.

• Codes

  • 0 No treatment given
  • 1 Treatment given
  • 2 Active surveillance (watchful waiting)
  • 9 Unknown if treatment was given

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1285

All data

st_css() #IMPORTANT!

  rxsummtreatmentstatus <- as.factor(trimws(d[,"rxsummtreatmentstatus"]))
  levels(rxsummtreatmentstatus) <- list(    No_treatment_given.0="0",
                                          Treatment_given.1="1",
                                          Active.2="2",
                                          Unknown.9="9"
                                          )
    rxsummtreatmentstatus <- relevel(rxsummtreatmentstatus, ref="Treatment_given.1")
    new.d <- data.frame(new.d, rxsummtreatmentstatus)
    new.d <- apply_labels(new.d, rxsummtreatmentstatus = "Status for all treatment modalities")
    #summary(new.d$rxsummtreatmentstatus)
temp.d <- data.frame (new.d.1, rxsummtreatmentstatus)
summarytools::view(dfSummary(new.d$rxsummtreatmentstatus, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummtreatmentstatus [labelled, factor]	Status for all treatment modalities	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	1829 ( 84.4% ) 207 ( 9.6% ) 117 ( 5.4% ) 14 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	154 ( 81.5% ) 15 ( 7.9% ) 15 ( 7.9% ) 5 ( 2.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	126 ( 72.4% ) 12 ( 6.9% ) 34 ( 19.5% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	205 ( 86.5% ) 12 ( 5.1% ) 17 ( 7.2% ) 3 ( 1.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	141 ( 81.0% ) 19 ( 10.9% ) 14 ( 8.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	264 ( 91.0% ) 16 ( 5.5% ) 6 ( 2.1% ) 4 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	928 ( 85.4% ) 130 ( 12.0% ) 29 ( 2.7% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_treatment_status [factor]	1. Treatment_given.1 2. No_treatment_given.0 3. Active.2 4. Unknown.9	11 ( 68.8% ) 3 ( 18.8% ) 2 ( 12.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SURG PRIM SITE

• Description: Site-specific codes for the type of surgery to the primary site performed as part of the first course of treatment. This includes treatment given at all facilities as part of the first course of treatment.

• Codes: (in addition to the site-specific codes; Refer to the most recent version of STORE and SEER Program Code manual for additional instructions.)

  • 00 None
  • 10-19 Site-specific code; tumor destruction
  • 20-80 Site-specific codes; resection
  • 90 Surgery, NOS
  • 98 Site specific codes; special
  • 99 Unknown

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1290

All data

st_css() #IMPORTANT!

  # Put 10-19 into one catecory and 20-80 into one category
  a<-as.numeric(d$rxsummsurgprimsite)
  a[which(a>=10&a<=19)]<-10
  a[which(a>=20&a<=80)]<-20
  rxsummsurgprimsite <- as.factor(a)
  levels(rxsummsurgprimsite) <- list(None.0="0",
                                  Tumor_destruction.10="10",
                                  Resection.20="20",
                                  Surgery_NOS.90="90",
                                  Unknown.99="99"
                                  )
    new.d <- data.frame(new.d, rxsummsurgprimsite)
    new.d <- apply_labels(new.d, rxsummsurgprimsite = "Type of radiation therapy")
    #summary(new.d$rxsummsurgprimsite)
temp.d <- data.frame (new.d.1, rxsummsurgprimsite)
summarytools::view(dfSummary(new.d$rxsummsurgprimsite, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummsurgprimsite [labelled, factor]	Type of radiation therapy	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	1148 ( 53.0% ) 12 ( 0.6% ) 1002 ( 46.2% ) 0 ( 0.0% ) 5 ( 0.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	84 ( 44.4% ) 1 ( 0.5% ) 104 ( 55.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	126 ( 72.4% ) 0 ( 0.0% ) 48 ( 27.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	92 ( 38.8% ) 1 ( 0.4% ) 143 ( 60.3% ) 0 ( 0.0% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	89 ( 51.1% ) 1 ( 0.6% ) 84 ( 48.3% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	104 ( 35.9% ) 1 ( 0.3% ) 181 ( 62.4% ) 0 ( 0.0% ) 4 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	644 ( 59.2% ) 7 ( 0.6% ) 436 ( 40.1% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_prim_site [factor]	1. None.0 2. Tumor_destruction.10 3. Resection.20 4. Surgery_NOS.90 5. Unknown.99	9 ( 56.2% ) 1 ( 6.2% ) 6 ( 37.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SCOPE REG LN SUR

• Description: Describes the removal, biopsy or aspiration of regional lymph node(s) at the time of surgery of the primary site or during a separate surgical event at all facilities.

• Rationale: In evaluating quality-of-care and treatment practices it is important to identify the removal, biopsy, or aspiration of regional lymph node(s) at the time of surgery of the primary site or during a separate surgical event.

• Codes (Refer to the most recent versions of STORE and the SEER Program Code Manual for instructions that should be applied to all surgically treated cases for all types of cancers.) The treatment of breast and skin cancers are where the distinction between sentinel lymph node biopsies (SLNBx) and more extensive dissection of regional lymph nodes is most frequently encountered. For all other sites, non-sentinel regional node dissections are typical, and codes 2, 6 and 7 are infrequently used.

  • 0 None
  • 1 Biopsy or aspiration of regional lymph node, NOS
  • 2 Sentinel lymph node biopsy
  • 3 Number of regional lymph nodes removed unknown, not stated; regional lymph nodes removed, NOS
  • 4 1 to 3 regional lymph nodes removed
  • 5 4 or more regional lymph nodes removed
  • 6 Sentinel node biopsy and code 3, 4, or 5 at same time or timing not noted
  • 7 Sentinel node biopsy and code 3, 4, or 5 at different times
  • 9 Unknown or not applicable

• Note: One important use of registry data is the tracking of treatment patterns over time. To compare contemporary treatment to previously published treatment based on former codes, or to data unmodified from pre-1998 definitions, the ability to differentiate surgeries in which four or more regional lymph nodes are removed is desirable. However, it is very important to note that the distinction between codes 4 and 5 is made to permit comparison of current surgical procedures with procedures coded in the past when the removal of fewer than 4 nodes was not reflected in surgery codes. It is not intended to reflect clinical significance when applied to a particular surgical procedure. It is important to avoid inferring, by data presentation or other methods, that one category is preferable to another within the intent of these items.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1292

All data

st_css() #IMPORTANT!

  # Put 10-19 into one catecory and 20-80 into one category
  rxsummscopereglnsur <- as.factor(trimws(d[,"rxsummscopereglnsur"]))
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="0"] <- "None.0"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="1"] <- "Biopsy_or_aspiration_nodes.1"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="2"] <- "Sentinel_biopsy.2"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="3"] <- "Number_of_removed_unknown.3"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="4"] <- "1_3_removed.4"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="5"] <- "4_more_removed.5"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="6"] <- "code_345_same_time.6"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="7"] <- "code_345_diff_time.7"
  levels(rxsummscopereglnsur)[levels(rxsummscopereglnsur)=="9"] <- "Unknown.9"
  
  
    new.d <- data.frame(new.d, rxsummscopereglnsur)
    new.d <- apply_labels(new.d, rxsummscopereglnsur = "rx_summ_scope_reg_ln_sur")
    #summary(new.d$rxsummsurgprimsite)
temp.d <- data.frame (new.d.1, rxsummscopereglnsur)
summarytools::view(dfSummary(new.d$rxsummscopereglnsur, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummscopereglnsur [labelled, factor]	rx_summ_scope_reg_ln_sur	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	1460 ( 67.4% ) 3 ( 0.1% ) 1 ( 0.0% ) 8 ( 0.4% ) 171 ( 7.9% ) 517 ( 23.9% ) 2 ( 0.1% ) 5 ( 0.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	124 ( 65.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 4.8% ) 56 ( 29.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	137 ( 78.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 7 ( 4.0% ) 30 ( 17.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	131 ( 55.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 24 ( 10.1% ) 80 ( 33.8% ) 0 ( 0.0% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	103 ( 59.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.7% ) 10 ( 5.7% ) 58 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	121 ( 41.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 56 ( 19.3% ) 106 ( 36.6% ) 0 ( 0.0% ) 4 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	833 ( 76.6% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 63 ( 5.8% ) 184 ( 16.9% ) 2 ( 0.2% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_scope_reg_ln_sur [factor]	1. None.0 2. Biopsy_or_aspiration_node 3. Sentinel_biopsy.2 4. Number_of_removed_unknown 5. 1_3_removed.4 6. 4_more_removed.5 7. code_345_same_time.6 8. Unknown.9	11 ( 68.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 12.5% ) 3 ( 18.8% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SURG OTH REG/DIS

• Description: Records the surgical removal of distant lymph nodes or other tissue(s)/organ(s) beyond the primary site.
• Rationale: The removal of non-primary tissue documents the extent of surgical treatment and is useful in evaluating the extent of metastatic involvement.
• Codes (Refer to the most recent version of STORE and SEER Program Code Manual for additional instructions.)
  • 0 None; diagnosed at autopsy
  • 1 Non-primary surgical procedure performed
  • 2 Non-primary surgical procedure to other regional sites
  • 3 Non-primary surgical procedure to distant lymph node(s)
  • 4 Non-primary surgical procedure to distant site
  • 5 Any combination of codes 2, 3, or 4
  • 9 Unknown; death certificate only
• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1294

All data

st_css() #IMPORTANT!

  # Put 10-19 into one catecory and 20-80 into one category
  rxsummsurgothregdis <- as.factor(trimws(d[,"rxsummsurgothregdis"]))
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="0"] <- "None.0"
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="1"] <- "Procedure_performed.1"
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="2"] <- "Other_regional_sites.2"
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="3"] <- "Distant_lymph_node.3"
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="4"] <- "Distant_site.4"
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="5"] <- "Combination_of_234.5"
  levels(rxsummsurgothregdis)[levels(rxsummsurgothregdis)=="9"] <- "Unknown.9"
  
  
    new.d <- data.frame(new.d, rxsummsurgothregdis)
    new.d <- apply_labels(new.d, rxsummsurgothregdis = "rx_summ_surg_oth_reg_dis")
    #summary(new.d$rxsummsurgprimsite)
temp.d <- data.frame (new.d.1, rxsummsurgothregdis)
summarytools::view(dfSummary(new.d$rxsummsurgothregdis, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummsurgothregdis [labelled, factor]	rx_summ_surg_oth_reg_dis	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	2145 ( 99.0% ) 6 ( 0.3% ) 4 ( 0.2% ) 4 ( 0.2% ) 2 ( 0.1% ) 6 ( 0.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	188 ( 99.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	234 ( 98.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	283 ( 97.6% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 5 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	1077 ( 99.1% ) 5 ( 0.5% ) 3 ( 0.3% ) 2 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_oth_reg_dis [factor]	1. None.0 2. Procedure_performed.1 3. Other_regional_sites.2 4. Distant_lymph_node.3 5. Combination_of_234.5 6. Unknown.9	15 ( 93.8% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

REASON FOR NO SURGERY

• Description: Records the reason that no surgery was performed on the primary site.
• Rationale: This data item provides information related to the quality of care and describes why primary site surgery was not performed.
• Codes
  • 0 Surgery of the primary site was performed.
  • 1 Surgery of the primary site was not performed because it was not part of the planned first-course treatment.
  • 2 Surgery of the primary site was not recommended/performed because it was contraindicated due to patient risk factors (comorbid conditions, advanced age, etc.).
  • 5 Surgery of the primary site was not performed because the patient died prior to planned or recommended surgery.
  • 6 Surgery of the primary site was not performed; it was recommended by the patient’s physician, but was not performed as part of the first-course therapy. No reason was noted in the patient’s record.
  • 7 Surgery of the primary site was not performed; it was recommended by the patient’s physician, but this treatment was refused by the patient, the patient’s family member, or the patient’s guardian. The refusal was noted in the patient record.
  • 8 Surgery of the primary site was recommended, but it is unknown if it was performed. Further follow-up is recommended.
  • 9 It is unknown if surgery of the primary site was recommended or performed. Death certificate-only cases and autopsy-only cases.
• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1340

All data

st_css() #IMPORTANT!

  # Put 10-19 into one catecory and 20-80 into one category
  reasonfornosurgery <- as.factor(trimws(d[,"reasonfornosurgery"]))
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="0"] <- "Site_performed.0"
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="1"] <- "not_part_of_planned.1"
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="2"] <- "Other_regional_sites.2"
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="6"] <- "not_first_course_therapy.6"
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="7"] <- "Recommended_refused.7"
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="8"] <- "Recommended_unknown.8"
  levels(reasonfornosurgery)[levels(reasonfornosurgery)=="9"] <- "Unknown.9"
  
  
    new.d <- data.frame(new.d, reasonfornosurgery)
    new.d <- apply_labels(new.d, reasonfornosurgery = "reason_for_no_surgery")
    #summary(new.d$rxsummsurgprimsite)
temp.d <- data.frame (new.d.1, reasonfornosurgery)
summarytools::view(dfSummary(new.d$reasonfornosurgery, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reasonfornosurgery [labelled, factor]	reason_for_no_surgery	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	1014 ( 46.8% ) 1063 ( 49.1% ) 30 ( 1.4% ) 3 ( 0.1% ) 32 ( 1.5% ) 20 ( 0.9% ) 5 ( 0.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	105 ( 55.6% ) 71 ( 37.6% ) 2 ( 1.1% ) 0 ( 0.0% ) 6 ( 3.2% ) 5 ( 2.6% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	48 ( 27.6% ) 120 ( 69.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 4 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	144 ( 60.8% ) 86 ( 36.3% ) 1 ( 0.4% ) 0 ( 0.0% ) 4 ( 1.7% ) 1 ( 0.4% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	85 ( 48.9% ) 81 ( 46.6% ) 5 ( 2.9% ) 1 ( 0.6% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	182 ( 62.8% ) 89 ( 30.7% ) 9 ( 3.1% ) 1 ( 0.3% ) 2 ( 0.7% ) 3 ( 1.0% ) 4 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	443 ( 40.8% ) 607 ( 55.8% ) 11 ( 1.0% ) 1 ( 0.1% ) 14 ( 1.3% ) 11 ( 1.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	reason_for_no_surgery [factor]	1. Site_performed.0 2. not_part_of_planned.1 3. Other_regional_sites.2 4. not_first_course_therapy. 5. Recommended_refused.7 6. Recommended_unknown.8 7. Unknown.9	7 ( 43.8% ) 9 ( 56.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–RADIATION

• Description: Codes for the type of radiation therapy performed as part of the first course of treatment. Note: Radiation to brain and central nervous system for leukemia and lung cases is coded as radiation in this field.

• Codes

  • 0 None
  • 1 Beam radiation
  • 2 Radioactive implants
  • 3 Radioisotopes
  • 4 Combination of 1 with 2 or 3
  • 5 Radiation, NOS-method or source not specified
  • 6 Currently allowable for historic cases only; see note below
  • 7 Patient or patient’s guardian refused*
  • 8 Radiation recommended, unknown if administered*
  • 9 Unknown if radiation administered

• Note: CoC discontinued collection of this item in 2003 when FORDS was implemented. For CoC, codes 7 and 8 were used for tumors diagnosed before 1996, but should have been converted to 0 in this field and to the appropriate code in the new field Reason for No Radiation [1430]. SEER continues to use codes 7 and 8 for all years. See Chapter V, Unresolved Issues, for further discussion.

• In the SEER program, a code 2 for other radiation was used between 1973 and 1987. When the radiation codes were expanded to add codes ‘2’ radioactive implants and ‘3’ radioisotopes, all cases with a code ‘2’ and diagnosed in 1973-1987 were converted to a code ‘6’ radiation other than beam radiation.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1360

All data

st_css() #IMPORTANT!

  rxsummradiation <- as.factor(trimws(d[,"rxsummradiation"]))
  levels(rxsummradiation) <- list(None.0="0",
                                  Beam_radiation.1="1",
                                  Radioactive_implants.2="2",
                                  Radioisotopes.3="3",
                                  Combination_12_or_13.4="4",
                                  NOS_or_source_not_specified.5="5",
                                  Historic_cases_only.6="6",
                                  Refused.7="7",
                                  Radiation_recommended_unknown.8="8",
                                  Unknown.9 = "9")
    new.d <- data.frame(new.d, rxsummradiation)
    new.d <- apply_labels(new.d, rxsummradiation = "Type of radiation therapy")
    #summary(new.d$rxsummradiation)
temp.d <- data.frame (new.d.1, rxsummradiation)
summarytools::view(dfSummary(new.d$rxsummradiation, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummradiation [labelled, factor]	Type of radiation therapy	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	1254 ( 58.5% ) 546 ( 25.5% ) 124 ( 5.8% ) 3 ( 0.1% ) 149 ( 7.0% ) 3 ( 0.1% ) 0 ( 0.0% ) 12 ( 0.6% ) 41 ( 1.9% ) 11 ( 0.5% )		24 (1.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	129 ( 68.3% ) 42 ( 22.2% ) 4 ( 2.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.6% ) 8 ( 4.2% ) 1 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	96 ( 55.2% ) 50 ( 28.7% ) 16 ( 9.2% ) 0 ( 0.0% ) 12 ( 6.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	165 ( 69.6% ) 45 ( 19.0% ) 10 ( 4.2% ) 0 ( 0.0% ) 3 ( 1.3% ) 1 ( 0.4% ) 0 ( 0.0% ) 6 ( 2.5% ) 5 ( 2.1% ) 2 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	103 ( 67.8% ) 36 ( 23.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.3% ) 2 ( 1.3% )		22 (12.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	185 ( 63.8% ) 92 ( 31.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 5 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 6 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	565 ( 52.1% ) 277 ( 25.5% ) 92 ( 8.5% ) 3 ( 0.3% ) 118 ( 10.9% ) 2 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.2% ) 26 ( 2.4% ) 0 ( 0.0% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_radiation [factor]	1. None.0 2. Beam_radiation.1 3. Radioactive_implants.2 4. Radioisotopes.3 5. Combination_12_or_13.4 6. NOS_or_source_not_specifi 7. Historic_cases_only.6 8. Refused.7 9. Radiation_recommended_unk 10. Unknown.9	11 ( 68.8% ) 4 ( 25.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SURG/RAD SEQ

• Description: Codes for the sequencing of radiation and surgery given as part of the first course of treatment. See also RX Summ–Surg Prim Site [1290], RX Summ–Scope LN Surg [1292], RX Summ–Surg Oth Reg/Dis [1294], and RX Summ–Radiation [1360].

• Codes

  • 0 No radiation and/or no surgery; unknown if surgery and/or radiation given
  • 2 Radiation before surgery
  • 3 Radiation after surgery
  • 4 Radiation both before and after surgery
  • 5 Intraoperative radiation
  • 6 Intraoperative radiation with other radiation given before and/or after surgery
  • 7 Surgery both before and after radiation
  • 9 Sequence unknown, but both surgery and radiation were given

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1380

All data

st_css() #IMPORTANT!

  rxsummsurgradseq <- as.factor(trimws(d[,"rxsummsurgradseq"]))
  levels(rxsummsurgradseq) <- list(No_radiation_surgery.0="0",
                                  Before_surgery.2="2",
                                  After_surgery.3="3",
                                  Both_before_after_surg.4="4",
                                  Intraoperative_radiation.5="5",
                                  Intraoperative_with_other.6="6",
                                  Both_before_after_radia.7="7",
                                  Unknown_Sequence.9 = "9")
    new.d <- data.frame(new.d, rxsummsurgradseq)
    new.d <- apply_labels(new.d, rxsummsurgradseq = "rx_summ_surg_rad_seq")
    #summary(new.d$rxsummsurgradseq)
temp.d <- data.frame (new.d.1, rxsummsurgradseq)
summarytools::view(dfSummary(new.d$rxsummsurgradseq, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummsurgradseq [labelled, factor]	rx_summ_surg_rad_seq	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	2059 ( 95.0% ) 3 ( 0.1% ) 101 ( 4.7% ) 0 ( 0.0% ) 1 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	184 ( 97.4% ) 1 ( 0.5% ) 4 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	169 ( 97.1% ) 0 ( 0.0% ) 5 ( 2.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	229 ( 96.6% ) 0 ( 0.0% ) 7 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	161 ( 92.5% ) 0 ( 0.0% ) 13 ( 7.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	267 ( 92.1% ) 0 ( 0.0% ) 22 ( 7.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	1034 ( 95.1% ) 2 ( 0.2% ) 49 ( 4.5% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_surg_rad_seq [factor]	1. No_radiation_surgery.0 2. Before_surgery.2 3. After_surgery.3 4. Both_before_after_surg.4 5. Intraoperative_radiation. 6. Intraoperative_with_other 7. Both_before_after_radia.7 8. Unknown_Sequence.9	15 ( 93.8% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–CHEMO

• Description: Codes for chemotherapy given as part of the first course of treatment or the reason chemotherapy was not given. Includes treatment given at all facilities as part of the first course. Note: Prior to 2013, targeted therapies that invoke an immune response, such as Herceptin, had been coded as chemotherapy. Effective with cases diagnosed January 1, 2013, and forward these therapies are classified as biological response modifiers. Coding instructions for these changes have been added to the remarks field for the applicable drugs in the SEER*RX Interactive Drug Database ( http://seer.cancer.gov/tools/seerrx/).

• Codes (Refer to the most recent version of STORE for additional instructions.)

  • 00 None, chemotherapy was not part of the planned first course of therapy.
  • 01 Chemotherapy, NOS.
  • 02 Chemotherapy, single agent.
  • 03 Chemotherapy, multiple agents.
  • 82 Chemotherapy was not recommended/administered because it was contraindicated due to patient risk factors (i.e., comorbid conditions, advanced age).
  • 85 Chemotherapy was not administered because the patient died prior to planned or recommended therapy.
  • 86 Chemotherapy was not administered. It was recommended by the patient’s physician, but was not administered as part of first-course therapy. No reason was stated in the patient record.
  • 87 Chemotherapy was not administered; it was recommended by the patient’s physician, but this treatment was refused by the patient, the patient’s family member, or the patient’s guardian. The refusal was noted in the patient record.
  • 88 Chemotherapy was recommended, but it is unknown if it was administered.
  • 99 It is unknown whether a chemotherapeutic agent(s) was recommended or administered because it is not stated in patient record; death certificate-only cases.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1390

All data

st_css() #IMPORTANT!

  rxsummchemo <- as.factor(trimws(d[,"rxsummchemo"]))
  levels(rxsummchemo) <- list(None.0="0",
                                  Chemo_NOS.1="1",
                                  Chemo_single_agent.2="2",
                                  Chemo_multiple_agents.3="3",
                                  Not_recom_contraindicated.82="82",
                                  Not_admin_first_course_trp.86="86",
                                  Not_admin_refused.87="87",
                                  Unknown_if_administered.88="88",
                                  unknown.99="99")
    new.d <- data.frame(new.d, rxsummchemo)
    new.d <- apply_labels(new.d, rxsummchemo = "Chemotherapy as part of the first course of treatment")
    #summary(new.d$rxsummchemo)
temp.d <- data.frame (new.d.1, rxsummchemo)
summarytools::view(dfSummary(new.d$rxsummchemo, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummchemo [labelled, factor]	Chemotherapy as part of the first course of treatment	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	2121 ( 97.9% ) 1 ( 0.0% ) 24 ( 1.1% ) 4 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.0% ) 4 ( 0.2% ) 12 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	188 ( 99.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	170 ( 97.7% ) 0 ( 0.0% ) 4 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	229 ( 96.6% ) 0 ( 0.0% ) 7 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	278 ( 95.9% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 3.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	1066 ( 98.1% ) 1 ( 0.1% ) 11 ( 1.0% ) 4 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 4 ( 0.4% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_chemo [factor]	1. None.0 2. Chemo_NOS.1 3. Chemo_single_agent.2 4. Chemo_multiple_agents.3 5. Not_recom_contraindicated 6. Not_admin_first_course_tr 7. Not_admin_refused.87 8. Unknown_if_administered.8 9. unknown.99	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–HORMONE

• Description: Records whether systemic hormonal agents were administered as first-course treatment at any facility, or the reason they were not given. Hormone therapy consists of a group of drugs that may affect the long-term control of a cancer’s growth. It is not usually used as a curative measure.

• Rationale: Systemic therapy may involve the administration of one or a combination of agents. This data item allows for the evaluation of the administration of hormonal agents as part of the first course of therapy.

• Codes (Refer to the most recent version of STORE and the SEER Program Code Manual for additional instructions.)

  • 00 None, hormone therapy was not part of the planned first course of therapy.
  • 01 Hormone therapy administered as first course therapy.
  • 82 Hormone therapy was not recommended/administered because it was contraindicated due to patient risk factors (i.e., comorbid conditions, advanced age).
  • 85 Hormone therapy was not administered because the patient died prior to planned or recommended therapy.
  • 86 Hormone therapy was not administered. It was recommended by the patient’s physician, but was not administered as part of first-course therapy. No reason was stated in the patient record.
  • 87 Hormone therapy was not administered. It was recommended by the patient’s physician, but this treatment was refused by the patient, the patient’s family member, or the patient’s guardian. The refusal was noted in the patient record.
  • 88 Hormone therapy was recommended, but it is unknown if it was administered.
  • 99 It is unknown whether a hormonal agent(s) was recommended or administered because it is not stated in the patient record. Death certificate-only cases.

• Note: For tumors diagnosed on or after January 1, 2003, information on endocrine surgery and/or endocrine radiation should be coded in the new field, RX Summ–Transplnt/Endocr [3250]. The CoC standards for hospitals do not allow use of codes 02-03 in tumors diagnosed on or after January 1, 2003.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1400

All data

st_css() #IMPORTANT!

  rxsummhormone <- as.factor(trimws(d[,"rxsummhormone"]))
  levels(rxsummhormone) <- list(None.0="0",
                              HT_first_course.1="1",
                              Not_recom_contraindicated.82="82",
                              Not_admin_died.85="85",
                              Recom_not_admin.86="86",
                              Recomm_but_refused.87="87",
                              Unknown_if_admin.88="88",
                              Unknown.99="99")
    new.d <- data.frame(new.d, rxsummhormone)
    new.d <- apply_labels(new.d, rxsummhormone = "Hormonal agents as part of the first course of treatment")
    #summary(new.d$rxsummhormone)
temp.d <- data.frame (new.d.1, rxsummhormone)
summarytools::view(dfSummary(new.d$rxsummhormone, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummhormone [labelled, factor]	Hormonal agents as part of the first course of treatment	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	1633 ( 75.4% ) 471 ( 21.7% ) 2 ( 0.1% ) 0 ( 0.0% ) 5 ( 0.2% ) 21 ( 1.0% ) 18 ( 0.8% ) 17 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	148 ( 78.3% ) 38 ( 20.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	125 ( 71.8% ) 46 ( 26.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	188 ( 79.3% ) 43 ( 18.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 2 ( 0.8% ) 2 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	129 ( 74.1% ) 43 ( 24.7% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	200 ( 69.0% ) 77 ( 26.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.0% ) 10 ( 3.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	828 ( 76.2% ) 223 ( 20.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 0.4% ) 14 ( 1.3% ) 13 ( 1.2% ) 5 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_hormone [factor]	1. None.0 2. HT_first_course.1 3. Not_recom_contraindicated 4. Not_admin_died.85 5. Recom_not_admin.86 6. Recomm_but_refused.87 7. Unknown_if_admin.88 8. Unknown.99	15 ( 93.8% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–BRM

• Description:Records whether immunotherapeutic (biologic response modifiers) agents were administered as first-course treatment at all facilities or the reason they were not given. Immunotherapy consists of biological or chemical agents that alter the immune system or change the host’s response to tumor cells.

• Rationale: Systemic therapy may involve the administration of one or a combination of agents. This data item allows for the evaluation of the administration of immunotherapeutic agents as part of the first course of therapy.

• Note: Prior to 2013, targeted therapies that invoke an immune response, such as Herceptin, had been coded as chemotherapy. Effective with cases diagnosed January 1, 2013, and forward these therapies are classified as biological response modifiers. Coding instructions for these changes have been added to the remarks field for the applicable drugs in the SEER*RX Interactive Drug Database ( http://seer.cancer.gov/tools/seerrx/).

• Codes (Refer to the most recent version of STORE and the SEER Program Code Manual for additional instructions.)

  • 00 None, immunotherapy was not part of the planned first course of therapy.
  • 01 Immunotherapy administered as first course therapy.
  • 82 Immunotherapy was not recommended/administered because it was contraindicated due to patient risk factors (i.e., comorbid conditions, advanced age).
  • 85 Immunotherapy was not administered because the patient died prior to planned or recommended therapy.
  • 86 Immunotherapy was not administered. It was recommended by the patient’s physician, but was not administered as part of first-course therapy. No reason was stated in the patient record.
  • 87 Immunotherapy was not administered. It was recommended by the patient’s physician, but this treatment was refused by the patient, the patient’s family member, or the patient’s guardian. The refusal was noted in the patient record.
  • 88 Immunotherapy was recommended, but it is unknown if it was administered.
  • 99 It is unknown whether an immunotherapeutic agent(s) was recommended or administered because it is not stated in patient record; death certificate-only cases.

• Note: For tumors diagnosed on or after January 1, 2003, information on bone marrow transplants and stem cell transplants should be coded in the new field, RX SUMM–Transplnt/Endocr [3250]. The CoC standards for hospitals do not allow use of codes 02-06 in tumors diagnosed on or after January 1, 2003.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1410

All data

st_css() #IMPORTANT!

  rxsummbrm <- as.factor(trimws(d[,"rxsummbrm"]))
  levels(rxsummbrm) <- list(None.0="0",
                              Immunotherapy_first_course.1="1",
                              Recomm_not_admin.86="86",
                              Unknown_if_admin.88="88",
                              Unknown.99="99")
    new.d <- data.frame(new.d, rxsummbrm)
    new.d <- apply_labels(new.d, rxsummbrm = "rx_summ_brm")
    #summary(new.d$rxsummbrm)
temp.d <- data.frame (new.d.1, rxsummbrm)
summarytools::view(dfSummary(new.d$rxsummbrm, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummbrm [labelled, factor]	rx_summ_brm	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	2149 ( 99.2% ) 5 ( 0.2% ) 1 ( 0.0% ) 1 ( 0.0% ) 11 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	189 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	236 ( 99.6% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	279 ( 96.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 3.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	1081 ( 99.4% ) 4 ( 0.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_brm [factor]	1. None.0 2. Immunotherapy_first_cours 3. Recomm_not_admin.86 4. Unknown_if_admin.88 5. Unknown.99	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–OTHER

• Description:Identifies other treatment given at all facilities that cannot be defined as surgery, radiation, or systemic therapy according to the defined data items in this manual. Treatment for reportable hematopoietic diseases can be supportive care, observation, or any treatment that does not meet the usual definition in which treatment modifies, controls, removes, or destroys proliferating cancer tissue. Such treatments include phlebotomy, transfusions, and aspirin.

• Rationale: Information on other therapy is used to describe and evaluate the quality-of-care and treatment practices.

• Codes (Refer to the most recent version of STORE and the SEER Program Code Manual for additional instructions.)

  • 0 None
  • 1 Other
  • 2 Other Experimental
  • 3 Other-Double Blind
  • 6 Other-Unproven
  • 7 Refusal
  • 8 Recommended
  • 9 Unknown; unknown if administered

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1420

All data

st_css() #IMPORTANT!

  rxsummother <- as.factor(trimws(d[,"rxsummother"]))
  levels(rxsummother) <- list(None.0="0",
                              Other.1="1",
                              Other_Unproven.86="6",
                              Unknown.9="9")
    new.d <- data.frame(new.d, rxsummother)
    new.d <- apply_labels(new.d, rxsummother = "rx_summ_other")
    #summary(new.d$rxsummother)
temp.d <- data.frame (new.d.1, rxsummother)
summarytools::view(dfSummary(new.d$rxsummother, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummother [labelled, factor]	rx_summ_other	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	2153 ( 99.4% ) 2 ( 0.1% ) 1 ( 0.0% ) 11 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	189 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	236 ( 99.6% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	279 ( 96.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 3.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	1085 ( 99.8% ) 2 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_other [factor]	1. None.0 2. Other.1 3. Other_Unproven.86 4. Unknown.9	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RAD–REGIONAL DOSE: CGY

• Description: The dominant or most clinically significant total dose of regional radiation therapy delivered to the patient during the first course of treatment. The unit of measure is centiGray (cGy). See also Rad–Regional RX Modality [1570].

• Codes (in addition to actual doses)

  • (Fill spaces) Record the actual regional dose delivered
  • 00000 Radiation therapy was not administered
  • 88888 Not applicable, brachytherapy or radioisotopes administered to the patient
  • 99999 Regional radiation therapy was administered, but the dose is unknown

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1510

All data

st_css() #IMPORTANT!

  radregionaldosecgy <- as.factor(trimws(d[,"radregionaldosecgy"]))

    new.d <- data.frame(new.d, radregionaldosecgy)
  new.d <- apply_labels(new.d, radregionaldosecgy = "rad_regional_dose_cgy")

temp.d <- data.frame (new.d.1, radregionaldosecgy)
summarytools::view(dfSummary(new.d$radregionaldosecgy, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	radregionaldosecgy [labelled, factor]	rad_regional_dose_cgy	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RAD–REGIONAL RX MODALITY

• Description: Records the dominant modality of radiation therapy used to deliver the clinically most significant regional dose to the primary volume of interest during the first course of treatment.

• Rationale: Radiation treatment frequently is delivered in two or more phases that can be summarized as regional and boost treatments. To evaluate patterns of radiation oncology care, it is necessary to know which radiation resources were employed in the delivery of therapy. For outcomes analysis, the modalities used for each of these phases can be very important.

• Codes

  • 00 No radiation treatment
  • 20 External beam, NOS
  • 21 Orthovoltage
  • 22 Cobalt-60, Cesium-137
  • 23 Photons (2-5 MV)
  • 24 Photons (6-10 MV)
  • 25 Photons (11-19 MV)
  • 26 Photons (> 19 MV)
  • 27 Photons (mixed energies)
  • 28 Electrons
  • 29 Photons and electrons mixed
  • 30 Neutrons, with or without photons/electrons
  • 31 IMRT
  • 32 Conformal or 3-D therapy
  • 40 Protons
  • 41 Stereotactic radiosurgery, NOS
  • 42 Linac radiosurgery
  • 43 Gamma Knife
  • 50 Brachytherapy, NOS
  • 51 Brachytherapy, Intracavitary, Low Dose Rate (LDR)
  • 52 Brachytherapy, Intracavitary, High Dose Rate (HDR)
  • 53 Brachytherapy, Interstitial, Low Dose Rate (LDR)
  • 54 Brachytherapy, Interstitial, High Dose Rate (HDR)
  • 55 Radium
  • 60 Radio-isotopes, NOS
  • 61 Strontium - 89
  • 62 Strontium - 90
  • 80* Combination modality, specified
  • 85* Combination modality, NOS
  • 98 Other, NOS
  • 99 Unknown

• Note: For tumors diagnosed prior to January 1, 2003, the codes reported in this data item describe any radiation administered to the patient as part or all of the first course of therapy.

• *Codes 80 and 85 describe specific converted descriptions of radiation therapy coded according to Volume II ROADS, and DAM rules and should only be used to record regional radiation for tumors diagnosed prior to January 1, 2003.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1570

All data

st_css() #IMPORTANT!

  radregionalrxmodality <- as.factor(trimws(d[,"radregionalrxmodality"]))
  levels(radregionalrxmodality) <- list(No_tx.0="0",
                                  External_beam.20="20",
                                  Photons_6_10_MV.24="24",
                                  Photons_11_19_MV.25="25",
                                  Photons_19more_MV.26="26",
                                  Photons_mixed.27="27",
                                  IMRT.31="31",
                                  Conformal_or_3D_therapy.32="32",
                                  Protons.40="40",
                                  Stereotactic_radiosurgery.41 = "41", 
                                  Linac_radiosurgery.42 = "42",
                                  Brachytherapy_NOS.50 = "50", 
                                  Brachytherapy_Intracavitary_LDR.51 = "51", 
                                  Brachytherapy_Intracavitary_HDR.52 = "52", 
                                  Brachytherapy_Interstitial_LDR.53 = "53",
                                  Brachytherapy_Interstitial_HDR.54 = "54",
                                  Radium.55 = "55", 
                                  Radio_isotopes.60 = "60", 
                                  Combination_modality_specified.80 = "80", 
                                  Other_NOS.98 = "98", 
                                  Unknown.99 = "99"
                                  )
    new.d <- data.frame(new.d, radregionalrxmodality)
    new.d <- apply_labels(new.d, radregionalrxmodality = "rad_regional_rx_modality")
    #summary(new.d$radregionalrxmodality)
temp.d <- data.frame (new.d.1, radregionalrxmodality)
summarytools::view(dfSummary(new.d$radregionalrxmodality, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	radregionalrxmodality [labelled, factor]	rad_regional_rx_modality	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.3 9. Protons.40 10. Stereotactic_radiosurgery 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavita 14. Brachytherapy_Intracavita 15. Brachytherapy_Interstitia 16. Brachytherapy_Interstitia 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_spec 20. Other_NOS.98 21. Unknown.99	1191 ( 60.3% ) 58 ( 2.9% ) 130 ( 6.6% ) 7 ( 0.4% ) 2 ( 0.1% ) 10 ( 0.5% ) 374 ( 18.9% ) 10 ( 0.5% ) 7 ( 0.4% ) 7 ( 0.4% ) 17 ( 0.9% ) 14 ( 0.7% ) 3 ( 0.2% ) 3 ( 0.2% ) 84 ( 4.3% ) 42 ( 2.1% ) 1 ( 0.1% ) 3 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.1% ) 9 ( 0.5% )		192 (8.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.3 9. Protons.40 10. Stereotactic_radiosurgery 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavita 14. Brachytherapy_Intracavita 15. Brachytherapy_Interstitia 16. Brachytherapy_Interstitia 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_spec 20. Other_NOS.98 21. Unknown.99	140 ( 74.1% ) 10 ( 5.3% ) 5 ( 2.6% ) 1 ( 0.5% ) 2 ( 1.1% ) 0 ( 0.0% ) 23 ( 12.2% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 3 ( 1.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.3 9. Protons.40 10. Stereotactic_radiosurgery 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavita 14. Brachytherapy_Intracavita 15. Brachytherapy_Interstitia 16. Brachytherapy_Interstitia 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_spec 20. Other_NOS.98 21. Unknown.99	96 ( 55.2% ) 7 ( 4.0% ) 13 ( 7.5% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.6% ) 33 ( 19.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 7 ( 4.0% ) 9 ( 5.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.3 9. Protons.40 10. Stereotactic_radiosurgery 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavita 14. Brachytherapy_Intracavita 15. Brachytherapy_Interstitia 16. Brachytherapy_Interstitia 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_spec 20. Other_NOS.98 21. Unknown.99	176 ( 74.3% ) 6 ( 2.5% ) 13 ( 5.5% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 24 ( 10.1% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.1% ) 5 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 2 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.32 9. Protons.40 10. Stereotactic_radiosurgery.41 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavitary_LDR.51 14. Brachytherapy_Intracavitary_HDR.52 15. Brachytherapy_Interstitial_LDR.53 16. Brachytherapy_Interstitial_HDR.54 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_specified.80 20. Other_NOS.98 21. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.3 9. Protons.40 10. Stereotactic_radiosurgery 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavita 14. Brachytherapy_Intracavita 15. Brachytherapy_Interstitia 16. Brachytherapy_Interstitia 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_spec 20. Other_NOS.98 21. Unknown.99	186 ( 64.1% ) 4 ( 1.4% ) 27 ( 9.3% ) 2 ( 0.7% ) 0 ( 0.0% ) 2 ( 0.7% ) 59 ( 20.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.3 9. Protons.40 10. Stereotactic_radiosurgery 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavita 14. Brachytherapy_Intracavita 15. Brachytherapy_Interstitia 16. Brachytherapy_Interstitia 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_spec 20. Other_NOS.98 21. Unknown.99	593 ( 54.7% ) 31 ( 2.9% ) 72 ( 6.6% ) 1 ( 0.1% ) 0 ( 0.0% ) 6 ( 0.6% ) 235 ( 21.7% ) 6 ( 0.6% ) 3 ( 0.3% ) 4 ( 0.4% ) 15 ( 1.4% ) 10 ( 0.9% ) 3 ( 0.3% ) 1 ( 0.1% ) 72 ( 6.6% ) 27 ( 2.5% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_regional_rx_modality [factor]	1. No_tx.0 2. External_beam.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_19more_MV.26 6. Photons_mixed.27 7. IMRT.31 8. Conformal_or_3D_therapy.32 9. Protons.40 10. Stereotactic_radiosurgery.41 11. Linac_radiosurgery.42 12. Brachytherapy_NOS.50 13. Brachytherapy_Intracavitary_LDR.51 14. Brachytherapy_Intracavitary_HDR.52 15. Brachytherapy_Interstitial_LDR.53 16. Brachytherapy_Interstitial_HDR.54 17. Radium.55 18. Radio_isotopes.60 19. Combination_modality_specified.80 20. Other_NOS.98 21. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SYSTEMIC/SUR SEQ

• Description: Records the sequencing of systemic therapy (RX Summ-Chemo [1390], RX Summ-Hormone [1400], RX Summ-BRM [1410], and RX Summ-Transplnt/Endocr [3250]) and surgical procedures given as part of the first course of treatment. See also RX Summ–Surg Prim Site [1290], RX Summ–Scope LN Surg [1292], and RX Summ–Surg Oth Reg/Dis [1294].

• Rationale: The sequence of systemic therapy and surgical procedures given as part of the first course of treatment cannot always be determined using the date on which each modality was started or performed. This data item can be used to more precisely evaluate the time of delivery of treatment to the patient.

• Codes

  • 0 No systemic therapy and/or surgical procedures; unknown if surgery and/or systemic therapy given
  • 2 Systemic therapy before surgery
  • 3 Systemic therapy after surgery
  • 4 Systemic therapy both before and after surgery
  • 5 Intraoperative systemic therapy
  • 6 Intraoperative systemic therapy with other therapy administered before and/or after surgery
  • 7 Surgery both before and after systemic therapy
  • 9 Sequence unknown, but both surgery and systemic therapy given

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1639

All data

st_css() #IMPORTANT!

  rxsummsystemicsurseq <- as.factor(trimws(d[,"rxsummsystemicsurseq"]))
  levels(rxsummsystemicsurseq) <- list(No.0="0",
                                  Therapy_before_surg.2="2",
                                  Therapy_after_surg.3="3",
                                  Both_before_after.4="4",
                                  Sequence_unknown_not_given.9="9"
                                  )
    new.d <- data.frame(new.d, rxsummsystemicsurseq)
    new.d <- apply_labels(new.d, rxsummsystemicsurseq = "rx_summ_systemic_sur_seq")
    #summary(new.d$rxsummsystemicsurseq)
temp.d <- data.frame (new.d.1, rxsummsystemicsurseq)
summarytools::view(dfSummary(new.d$rxsummsystemicsurseq, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummsystemicsurseq [labelled, factor]	rx_summ_systemic_sur_seq	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	2085 ( 96.2% ) 15 ( 0.7% ) 63 ( 2.9% ) 3 ( 0.1% ) 1 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	178 ( 94.2% ) 4 ( 2.1% ) 6 ( 3.2% ) 1 ( 0.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	169 ( 97.1% ) 2 ( 1.1% ) 3 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	228 ( 96.2% ) 4 ( 1.7% ) 4 ( 1.7% ) 1 ( 0.4% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	165 ( 94.8% ) 0 ( 0.0% ) 9 ( 5.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	278 ( 95.9% ) 2 ( 0.7% ) 9 ( 3.1% ) 0 ( 0.0% ) 1 ( 0.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	1051 ( 96.7% ) 3 ( 0.3% ) 32 ( 2.9% ) 1 ( 0.1% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_summ_systemic_sur_seq [factor]	1. No.0 2. Therapy_before_surg.2 3. Therapy_after_surg.3 4. Both_before_after.4 5. Sequence_unknown_not_give	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SURG SITE 98-02

• Description: Site-specific codes for the type of surgery to the primary site performed as part of the first course of treatment. This includes treatment given at all facilities as part of the first course of treatment. This field is to be used for ROADS codes after the ROADS to FORDS conversion. It is also to be used to code Surgery Primary Site at all facilities for all tumors diagnosed before January 1, 2003.
• Rationale: If central registries wish to study the treatment given at particular hospitals, the hospital-level treatment fields must be used.
• Codes (in addition to the site-specific codes)
  • 00 No primary site surgery performed
  • 99 Unknown if primary site surgery performed
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1646

All data

st_css() #IMPORTANT!

  rxsummsurgsite9802 <- as.factor(trimws(d[,"rxsummsurgsite9802"]))

    new.d <- data.frame(new.d, rxsummsurgsite9802)
  new.d <- apply_labels(new.d, rxsummsurgsite9802 = "rx_summ_surg_site_9802")

temp.d <- data.frame (new.d.1, rxsummsurgsite9802)
summarytools::view(dfSummary(new.d$rxsummsurgsite9802, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummsurgsite9802 [labelled, factor]	rx_summ_surg_site_9802	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SCOPE REG 98-02

• Description: Describes the removal, biopsy or aspiration of regional lymph node(s) at the time of surgery of the primary site or during a separate surgical event at all facilities. This field is to be used for ROADS codes after the ROADS to FORDS conversion. It is also to be used to code Scope of Regional Lymph Node Surgery at all facilities for all tumors diagnosed before January 1, 2003.
• Rationale: In evaluating quality of care and treatment practices it is important to identify the removal, biopsy, or aspiration of regional lymph node(s) at the time of surgery of the primary site or during a separate surgical event.
• Codes (See the CoC ROADS Manual 1998 Supplement and the SEER Program Code Manual for site-specific codes.)
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1647

All data

st_css() #IMPORTANT!

  rxsummscopereg9802 <- as.factor(trimws(d[,"rxsummscopereg9802"]))

    new.d <- data.frame(new.d, rxsummscopereg9802)
  new.d <- apply_labels(new.d, rxsummscopereg9802 = "rx_summ_scope_reg_9802")

temp.d <- data.frame (new.d.1, rxsummscopereg9802)
summarytools::view(dfSummary(new.d$rxsummscopereg9802, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummscopereg9802 [labelled, factor]	rx_summ_scope_reg_9802	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–SCOPE OTH 98-02

• Description: Records the surgical removal of distant lymph nodes or other tissue(s)/organ(s) beyond the primary site given at all facilities as part of the first course of treatment. This field is to be used for ROADS codes after the ROADS to FORDS conversion. It is also to be used to code Surgery Regional/Distant Sites at all facilities for all tumors diagnosed before January 1, 2003.
• Rationale: The removal of non-primary tissue documents the extent of surgical treatment and is useful in evaluating the extent of metastatic involvement.
• Codes (See the CoC ROADS Manual 1998 Supplement and the SEER Program Code Manual for site-specific codes.)
• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1648

All data

st_css() #IMPORTANT!

  rxsummsurgoth9802 <- as.factor(trimws(d[,"rxsummsurgoth9802"]))

    new.d <- data.frame(new.d, rxsummsurgoth9802)
  new.d <- apply_labels(new.d, rxsummsurgoth9802 = "rx_summ_surg_oth_9802")

temp.d <- data.frame (new.d.1, rxsummsurgoth9802)
summarytools::view(dfSummary(new.d$rxsummsurgoth9802, style = 'grid', max.distinct.values = 100, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummsurgoth9802 [labelled, factor]	rx_summ_surg_oth_9802	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DATE OF LAST CONTACT

• Description: Date of last contact with the patient, or date of death. If the patient has multiple tumors, Date of Last Contact should be the same for all tumors. See Chapter X for date format.

• Rationale: Used for recording Date of Last Contact from active or passive follow-up. Used to record date of death and to calculate survival.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1750

All data

st_css() #IMPORTANT!

  dateoflastcontact <- as.factor(d[,"dateoflastcontact"])
  
    new.d <- data.frame(new.d, dateoflastcontact)
    new.d <- apply_labels(new.d, dateoflastcontact = "date_of_last_contact")
    #summary(new.d$dateoflastcontact)
temp.d <- data.frame (new.d.1, dateoflastcontact)
summarytools::view(dfSummary(new.d$dateoflastcontact, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	dateoflastcontact [labelled, factor]	date_of_last_contact	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 8 ( 0.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 2107 ( 97.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor] EAN-8 codes	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 183 ( 96.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 173 ( 99.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor] EAN-8 codes	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 228 ( 96.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 172 ( 98.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 282 ( 97.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1053 ( 96.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	date_of_last_contact [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 201605  · 17. 20160519 18. 20160599 19. 201606  · 20. 20160708 21. 20160805 22. 20160812 23. 20161009 24. 20161031 25. 201611  · 26. 20161101 27. 20161103 28. 20161114 29. 20161121 30. 20161124 31. 20161199 32. 20161206 33. 20161208 34. 20161221 35. 201701  · 36. 20170103 37. 20170110 38. 20170111 39. 20170118 40. 20170124 41. 201702  · 42. 20170223 43. 201703  · 44. 20170306 45. 20170309 46. 20170330 47. 20170401 48. 20170404 49. 20170524 50. 20170609 [ 243 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

VITAL STATUS

• Description: Vital status of the patient as of the date entered in Date of Last Contact [1750]. If the patient has multiple tumors, vital status should be the same for all tumors.

• Codes

  • 0 Dead
  • 1 Alive

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1760

All data

st_css() #IMPORTANT!

  vitalstatus <- as.factor(trimws(d[,"vitalstatus"]))
  levels(vitalstatus) <- list(Dead.0="0",
                              Alive.1="1")
    new.d <- data.frame(new.d, vitalstatus)
    new.d <- apply_labels(new.d, vitalstatus = "Vital status of the patient")
    #summary(new.d$vitalstatus)
temp.d <- data.frame (new.d.1, vitalstatus)
summarytools::view(dfSummary(new.d$vitalstatus, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vitalstatus [labelled, factor]	Vital status of the patient	1. Dead.0 2. Alive.1	10 ( 0.5% ) 2157 ( 99.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	0 ( 0.0% ) 189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	2 ( 1.1% ) 172 ( 98.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	0 ( 0.0% ) 237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	3 ( 1.7% ) 171 ( 98.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	0 ( 0.0% ) 290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	5 ( 0.5% ) 1082 ( 99.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	vital_status [factor]	1. Dead.0 2. Alive.1	0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SURV-DATE ACTIVE FOLLOWUP

• Description: The Surv-Date Active Followup is defined as the earlier of the Date of Last Contact [1750] and a study cutoff date. The study cut-off date is a pre-determined date based on the year of data submission and is set in the survival program used to derive the seven survival variables. If the Date of Last Contact [1750] is earlier than the study cut-off date and either the day or month is unknown or not available, the values are imputed by the survival program. The survival program is available from your standard setter or NAACCR.

Example 1 Date of Last Contact: 20111120 Study Cut-off Date: 20111231 Surv-Date Active Followup: 20111120 Note: The date of last contact is earlier than the study cut-off date, and the date of last contact is complete, so the date of last contact is used in Surv-Date Active Followup.

Example 2 Date of Last Contact: 201111 Study Cut-off Date: 20111231 Surv-Date Active Followup: 20111115 Note: Rationale is to take mid-point of possible values. For Nov (30 days) it would be FLOOR((1+30)/2) = 15, where FLOOR is a function that rounds a decimal down to an integer.

• Rationale: The Surv-Date Active Followup is needed to be able to recalculate survival months if a different study cut-off date is used and provides flexibility to recalculate survival without needing to rerun the survival program on the original data. Additional information about the survival algorithm and what specific values are assigned in given missing date situations are available here: http://seer.cancer.gov/survivaltime/.

• Codes: If Date of Last Contact [1750] is blank, Surv-Date Active Followup will also be blank.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1782

All data

st_css() #IMPORTANT!

  survdateactivefollowup <- as.factor(d[,"survdateactivefollowup"])
  
    new.d <- data.frame(new.d, survdateactivefollowup)
    new.d <- apply_labels(new.d, survdateactivefollowup = "survdate_active_follow_up")
    #summary(new.d$survdateactivefollowup)
temp.d <- data.frame (new.d.1, survdateactivefollowup)
summarytools::view(dfSummary(new.d$survdateactivefollowup, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdateactivefollowup [labelled, factor]	survdate_active_follow_up	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 5 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1875 ( 97.2% )		237 (10.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor] EAN-8 codes	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 183 ( 96.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 173 ( 99.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 51. 20170724 52. 20170727 53. 201708  · 54. 20170811 55. 20170821 56. 20170830 57. 20171025 58. 20171206 59. 201801  · 60. 20180109 61. 20180118 62. 20180126 63. 20180201 64. 20180212 65. 20180219 66. 20180306 67. 20180307 68. 201804  · 69. 20180507 70. 20180509 71. 201806  · 72. 20180619 73. 20180625 74. 20180803 75. 20180810 76. 20180817 77. 20180820 78. 20180906 79. 20180908 80. 20181001 81. 20181005 82. 20181016 83. 20181025 84. 201811  · 85. 20181106 86. 20181107 87. 20181130 88. 20181199 89. 20181204 90. 20181214 91. 20181219 92. 20181231 93. 20181299 94. 201901  · 95. 201902  · 96. 201904  · 97. 201905  · 98. 201906  · 99. 201907  · 100. 201909  · 101. 201911  · 102. 201912  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 172 ( 98.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 281 ( 96.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 0 ( 0.0% ) 1050 ( 96.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_active_follow_up [factor]	1. 20150709 2. 20150722 3. 20150730 4. 20150810 5. 20150824 6. 20150915 7. 20151110 8. 20151113 9. 20151120 10. 20151216 11. 20160109 12. 20160322 13. 20160324 14. 20160402 15. 20160404 16. 20160519 17. 20160599 18. 20160708 19. 20160805 20. 20160812 21. 20161009 22. 20161031 23. 201611  · 24. 20161101 25. 20161103 26. 20161114 27. 20161121 28. 20161124 29. 20161199 30. 20161206 31. 20161208 32. 20161221 33. 20170103 34. 20170110 35. 20170111 36. 20170118 37. 20170124 38. 20170223 39. 201703  · 40. 20170306 41. 20170309 42. 20170330 43. 20170401 44. 20170404 45. 20170524 46. 20170609 47. 20170628 48. 20170711 49. 20170712 50. 20170713 [ 52 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SURV-DATE PRESUMED ALIVE

• Description: The Surv-Date Presumed Alive is the last date for which complete death ascertainment is available from the registry at the time a file is transmitted. Because not all central cancer registries conduct active patient follow-up, it is necessary to have an option for calculating survival times based on the assumption that the registry has ascertained all available deaths (state/province and national), and persons not known to be deceased are presumed to be alive as of the last date for which complete death ascertainment is available. This variable is set in the survival program used to derive the seven survival variables. The survival program is available from your standard setter or NAACCR.

Example 1 Vital Status: Alive Date of Last Contact: 20111120 Study Cut-off Date: 20111231 Latest date for complete death ascertainment: 20111231 Surv-Date Presumed Alive: 20111231

• Rationale: The Surv-Date Presumed Alive is needed to be able to recalculate survival months if a different study cut-off date is used and provides flexibility to recalculate survival without needing to rerun the survival program on the original data.

• Additional information about the survival algorithm and what specific values are assigned in given missing date situations are available here: http://seer.cancer.gov/survivaltime/.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1785

All data

st_css() #IMPORTANT!

  survdatepresumedalive <- as.factor(d[,"survdatepresumedalive"])
  
    new.d <- data.frame(new.d, survdatepresumedalive)
    new.d <- apply_labels(new.d, survdatepresumedalive = "survdate_presumed_alive")
    #summary(new.d$survdatepresumedalive)
temp.d <- data.frame (new.d.1, survdatepresumedalive)
summarytools::view(dfSummary(new.d$survdatepresumedalive, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdatepresumedalive [labelled, factor]	survdate_presumed_alive	1. 20181231 2. 20181299 3. 201912  ·	1551 ( 80.4% ) 190 ( 9.8% ) 189 ( 9.8% )		237 (10.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor] EAN-8 codes	1. 20181231 2. 20181299 3. 201912  ·	0 ( 0.0% ) 0 ( 0.0% ) 189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor]	1. 20181231 2. 20181299 3. 201912  ·	174 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor]	1. 20181231 2. 20181299 3. 201912  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor]	1. 20181231 2. 20181299 3. 201912  ·	0 ( 0.0% ) 174 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor]	1. 20181231 2. 20181299 3. 201912  ·	290 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor]	1. 20181231 2. 20181299 3. 201912  ·	1087 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_presumed_alive [factor]	1. 20181231 2. 20181299 3. 201912  ·	0 ( 0.0% ) 16 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SURV-DATE RX RECODE

• Description: The survival date of diagnosis recode is calculated using the month, day, and year of the Date of Diagnosis [390]. If the Date of Diagnosis [390] has complete month and day information, the Surv-Date Dx Recode will be the same as the Date of Diagnosis [390]. If the day or month is unknown or not available, the values are imputed by the survival program used to derive the seven survival variables. The survival program is available from your standard setter or NAACCR.

Example 1 Date of diagnosis: 20111199 Date of Last Contact: 20111120 Surv-Date of DX Recode: 20111110 Note: The recoded value is the mid-point between 11/1 and 11/20.

Example 2 Date of diagnosis: 2011 Date of Last Contact: 20111120 Surv-Date of DX Recode: 20110611 Note: The recoded value is the mid-point between 20110101 and 20111120.

• Rationale: The Surv-Date DX Recode is needed to be able to match to a lifetable entry to obtain expected survival. If a case is diagnosed in January 2000, the first 12 months of expected survival will be from the 2000 life table. If a case is diagnosed in December 2000, only one month will be from the 2000 life table and then the 2001 life table is used.

• Additional information about the survival algorithm and what specific values are assigned in given missing date situations are available here: http://seer.cancer.gov/survivaltime/.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1788

All data

st_css() #IMPORTANT!

  survdatedxrecode <- as.factor(d[,"survdatedxrecode"])
  
    new.d <- data.frame(new.d, survdatedxrecode)
    new.d <- apply_labels(new.d, survdatedxrecode = "survdate_dx_recode")
    #summary(new.d$survdatedxrecode)
temp.d <- data.frame (new.d.1, survdatedxrecode)
summarytools::view(dfSummary(new.d$survdatedxrecode, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdatedxrecode [labelled, factor]	survdate_dx_recode	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 8 ( 0.4% ) 3 ( 0.2% ) 5 ( 0.3% ) 4 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 5 ( 0.3% ) 4 ( 0.2% ) 4 ( 0.2% ) 3 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.2% ) 4 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.1% ) 4 ( 0.2% ) 3 ( 0.2% ) 6 ( 0.3% ) 4 ( 0.2% ) 1 ( 0.1% ) 4 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 3 ( 0.2% ) 1 ( 0.1% ) 3 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.1% ) 1816 ( 94.1% )		237 (10.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor] EAN-8 codes	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 177 ( 93.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor]	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 162 ( 93.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor]	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 51. 20150216 52. 20150217 53. 20150218 54. 20150220 55. 20150223 56. 20150224 57. 20150227 58. 20150299 59. 201503  · 60. 20150301 61. 20150302 62. 20150303 63. 20150304 64. 20150305 65. 20150306 66. 20150309 67. 20150310 68. 20150311 69. 20150312 70. 20150313 71. 20150315 72. 20150316 73. 20150317 74. 20150318 75. 20150319 76. 20150320 77. 20150323 78. 20150325 79. 20150326 80. 20150327 81. 20150330 82. 20150331 83. 20150399 84. 201504  · 85. 20150401 86. 20150403 87. 20150406 88. 20150407 89. 20150408 90. 20150410 91. 20150411 92. 20150413 93. 20150414 94. 20150415 95. 20150416 96. 20150417 97. 20150420 98. 20150421 99. 20150422 100. 20150423 101. 20150424 102. 20150427 103. 20150428 104. 20150429 105. 20150430 106. 20150499 107. 201505  · 108. 20150501 109. 20150502 110. 20150504 111. 20150505 112. 20150506 113. 20150507 114. 20150511 115. 20150512 116. 20150513 117. 20150514 118. 20150515 119. 20150519 120. 20150520 121. 20150521 122. 20150526 123. 20150527 124. 20150528 125. 20150529 126. 20150599 127. 201506  · 128. 20150601 129. 20150602 130. 20150603 131. 20150604 132. 20150605 133. 20150608 134. 20150609 135. 20150610 136. 20150611 137. 20150612 138. 20150615 139. 20150616 140. 20150617 141. 20150618 142. 20150619 143. 20150622 144. 20150623 145. 20150624 146. 20150625 147. 20150626 148. 20150629 149. 20150630 150. 20150699 151. 201507  · 152. 20150701 153. 20150702 154. 20150706 155. 20150707 156. 20150709 157. 20150710 158. 20150713 159. 20150714 160. 20150715 161. 20150716 162. 20150717 163. 20150720 164. 20150721 165. 20150722 166. 20150723 167. 20150724 168. 20150727 169. 20150728 170. 20150729 171. 20150730 172. 20150731 173. 20150799 174. 201508  · 175. 20150801 176. 20150803 177. 20150804 178. 20150805 179. 20150806 180. 20150807 181. 20150810 182. 20150811 183. 20150812 184. 20150813 185. 20150814 186. 20150815 187. 20150818 188. 20150819 189. 20150820 190. 20150821 191. 20150824 192. 20150825 193. 20150826 194. 20150827 195. 20150828 196. 20150831 197. 20150899 198. 201509  · 199. 20150901 200. 20150902 201. 20150908 202. 20150909 203. 20150910 204. 20150911 205. 20150912 206. 20150914 207. 20150915 208. 20150916 209. 20150917 210. 20150918 211. 20150921 212. 20150922 213. 20150924 214. 20150925 215. 20150928 216. 20150930 217. 20150999 218. 201510  · 219. 20151001 220. 20151005 221. 20151007 222. 20151008 223. 20151012 224. 20151013 225. 20151014 226. 20151015 227. 20151016 228. 20151019 229. 20151020 230. 20151021 231. 20151022 232. 20151023 233. 20151026 234. 20151027 235. 20151028 236. 20151029 237. 20151030 238. 20151099 239. 201511  · 240. 20151101 241. 20151102 242. 20151103 243. 20151104 244. 20151105 245. 20151106 246. 20151109 247. 20151110 248. 20151111 249. 20151112 250. 20151113 251. 20151116 252. 20151117 253. 20151119 254. 20151120 255. 20151123 256. 20151124 257. 20151127 258. 20151130 259. 20151199 260. 201512  · 261. 20151201 262. 20151202 263. 20151203 264. 20151204 265. 20151207 266. 20151208 267. 20151209 268. 20151210 269. 20151211 270. 20151214 271. 20151215 272. 20151216 273. 20151217 274. 20151218 275. 20151221 276. 20151223 277. 20151228 278. 20151229 279. 20151230 280. 20151299 281. 201601  · 282. 20160104 283. 20160105 284. 20160106 285. 20160107 286. 20160108 287. 20160111 288. 20160112 289. 20160113 290. 20160114 291. 20160115 292. 20160119 293. 20160120 294. 20160121 295. 20160122 296. 20160125 297. 20160126 298. 20160128 299. 20160129 300. 20160199 301. 201602  · 302. 20160201 303. 20160202 304. 20160203 305. 20160204 306. 20160205 307. 20160208 308. 20160209 309. 20160210 310. 20160211 311. 20160212 312. 20160215 313. 20160216 314. 20160217 315. 20160218 316. 20160219 317. 20160223 318. 20160224 319. 20160225 320. 20160226 321. 20160229 322. 20160299 323. 201603  · 324. 20160301 325. 20160302 326. 20160303 327. 20160304 328. 20160307 329. 20160308 330. 20160310 331. 20160311 332. 20160314 333. 20160315 334. 20160316 335. 20160317 336. 20160318 337. 20160321 338. 20160322 339. 20160323 340. 20160324 341. 20160325 342. 20160328 343. 20160329 344. 20160330 345. 20160331 346. 20160399 347. 201604  · 348. 20160401 349. 20160404 350. 20160405 351. 20160406 352. 20160407 353. 20160408 354. 20160411 355. 20160412 356. 20160413 357. 20160414 358. 20160415 359. 20160418 360. 20160419 361. 20160420 362. 20160421 363. 20160422 364. 20160425 365. 20160426 366. 20160427 367. 20160428 368. 20160429 369. 20160499 370. 201605  · 371. 20160502 372. 20160503 373. 20160504 374. 20160505 375. 20160506 376. 20160509 377. 20160510 378. 20160511 379. 20160512 380. 20160513 381. 20160516 382. 20160518 383. 20160519 384. 20160520 385. 20160523 386. 20160524 387. 20160525 388. 20160526 389. 20160527 390. 20160531 391. 20160599 392. 201606  · 393. 20160601 394. 20160602 395. 20160603 396. 20160606 397. 20160607 398. 20160608 399. 20160609 400. 20160610 401. 20160613 402. 20160614 403. 20160615 404. 20160616 405. 20160617 406. 20160620 407. 20160621 408. 20160622 409. 20160623 410. 20160624 411. 20160626 412. 20160628 413. 20160630 414. 20160699 415. 201607  · 416. 20160701 417. 20160705 418. 20160706 419. 20160707 420. 20160708 421. 20160711 422. 20160712 423. 20160713 424. 20160714 425. 20160715 426. 20160716 427. 20160718 428. 20160719 429. 20160720 430. 20160721 431. 20160722 432. 20160725 433. 20160726 434. 20160727 435. 20160728 436. 20160729 437. 20160799 438. 201608  · 439. 20160801 440. 20160802 441. 20160803 442. 20160804 443. 20160805 444. 20160808 445. 20160809 446. 20160810 447. 20160811 448. 20160812 449. 20160815 450. 20160816 451. 20160817 452. 20160818 453. 20160819 454. 20160822 455. 20160823 456. 20160824 457. 20160825 458. 20160826 459. 20160829 460. 20160830 461. 20160831 462. 20160899 463. 201609  · 464. 20160901 465. 20160902 466. 20160906 467. 20160907 468. 20160908 469. 20160909 470. 20160912 471. 20160913 472. 20160914 473. 20160915 474. 20160916 475. 20160919 476. 20160920 477. 20160921 478. 20160922 479. 20160923 480. 20160926 481. 20160928 482. 20160929 483. 20160930 484. 20160999 485. 201610  · 486. 20161001 487. 20161003 488. 20161004 489. 20161005 490. 20161006 491. 20161007 492. 20161010 493. 20161011 494. 20161012 495. 20161013 496. 20161014 497. 20161017 498. 20161018 499. 20161019 500. 20161020 501. 20161021 502. 20161024 503. 20161026 504. 20161027 505. 20161028 506. 20161031 507. 20161099 508. 201611  · 509. 20161101 510. 20161102 511. 20161103 512. 20161104 513. 20161107 514. 20161108 515. 20161109 516. 20161110 517. 20161114 518. 20161115 519. 20161116 520. 20161117 521. 20161118 522. 20161121 523. 20161122 524. 20161123 525. 20161128 526. 20161129 527. 20161130 528. 20161199 529. 201612  · 530. 20161201 531. 20161202 532. 20161205 533. 20161206 534. 20161207 535. 20161208 536. 20161209 537. 20161210 538. 20161212 539. 20161213 540. 20161214 541. 20161216 542. 20161219 543. 20161220 544. 20161221 545. 20161222 546. 20161223 547. 20161227 548. 20161228 549. 20161230 550. 20161299 551. 20170106 552. 20170199 553. 201702  · 554. 20170299 555. 201703  · 556. 20170399 557. 20170413 558. 20170499 559. 20170599 560. 201706  · 561. 20170699 562. 20170799 563. 201708  · 564. 20170899 565. 20170911 566. 20170999 567. 20171099 568. 201711  · 569. 20171199 570. 201712  · 571. 20171299 572. 20180199 573. 20180227 574. 20180299 575. 20180399 576. 20180499 577. 20180599 578. 20180699 579. 20180799 580. 20180899 581. 20180926 582. 20180999 583. 20181099 584. 20181199 585. 20181299	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor]	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 3.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 168 ( 96.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor]	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 276 ( 95.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor]	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.2% ) 4 ( 0.4% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 3 ( 0.3% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 4 ( 0.4% ) 2 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 3 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1032 ( 94.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	survdate_dx_recode [factor]	1. 20110899 2. 20120399 3. 20120499 4. 20120699 5. 20130199 6. 20130399 7. 20130499 8. 20130699 9. 20131099 10. 20140299 11. 20140399 12. 20140699 13. 20140799 14. 20141299 15. 201501  · 16. 20150101 17. 20150105 18. 20150106 19. 20150107 20. 20150108 21. 20150109 22. 20150112 23. 20150113 24. 20150114 25. 20150115 26. 20150116 27. 20150119 28. 20150120 29. 20150121 30. 20150122 31. 20150123 32. 20150126 33. 20150127 34. 20150128 35. 20150129 36. 20150130 37. 20150199 38. 201502  · 39. 20150201 40. 20150202 41. 20150203 42. 20150204 43. 20150205 44. 20150206 45. 20150209 46. 20150210 47. 20150211 48. 20150212 49. 20150213 50. 20150215 [ 535 others ]	1 ( 6.2% ) 1 ( 6.2% ) 2 ( 12.5% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

# CAUSE OF DEATH {.tabset} - Description: Official cause of death as coded from the death certificate in valid ICD-7, ICD-8, ICD-9, and ICD-10 codes. - Rationale: Cause of death is used for calculation of adjusted survival rates by the life table method. The adjustment corrects for deaths other than from the diagnosed cancer. - Note: This data item is no longer supported by CoC (as of January 1, 2003). - Special codes in addition to ICD-7, ICD-8, ICD-9, and ICD-10 (refer to SEER Program Code Manual for additional instructions.) + 0000 Patient alive at last contact + 7777 State death certificate not available + 7797 State death certificate available but underlying cause of death is not coded

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#1910

All data

st_css() #IMPORTANT!

  causeofdeath <- as.factor(trimws(d[,"causeofdeath"]))
  levels(causeofdeath) <- list(Alive_last_contact.0="0",
                                  Certificate_not_available.7777="7777"
                                )
    new.d <- data.frame(new.d, causeofdeath)
    new.d <- apply_labels(new.d, causeofdeath = "cause_of_death")
    #summary(new.d$causeofdeath)
temp.d <- data.frame (new.d.1, causeofdeath)
summarytools::view(dfSummary(new.d$causeofdeath, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	causeofdeath [labelled, factor]	cause_of_death	1. Alive_last_contact.0 2. Certificate_not_available	2157 ( 99.9% ) 2 ( 0.1% )		8 (0.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	189 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	172 ( 98.9% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	237 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	171 ( 100.0% ) 0 ( 0.0% )		3 (1.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	290 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	1082 ( 100.0% ) 0 ( 0.0% )		5 (0.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cause_of_death [factor]	1. Alive_last_contact.0 2. Certificate_not_available	16 ( 100.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS EXTENSION

• Description: Identifies contiguous growth (extension) of the primary tumor within the organ of origin or its direct extension into neighboring organs. For certain sites such as ovary, discontinuous metastasis is coded in CS Extension.

• Rationale: Tumor extension at diagnosis is a prognostic indicator used by Collaborative Staging to derive some TNM-T codes and some SEER Summary Stage codes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Note: For cases diagnosed prior to 2010, this was a 2 character field in CS version 1 which was converted to a 3 character field in CS version 2. Most 2 character codes were converted by adding a zero as the third character. For example, code 05 was usually converted to 050, 10 to 100, 11 to 110, etc. Special codes such as 88 and 99 were usually converted to 888 and 999, respectively.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2810

All data

st_css() #IMPORTANT!

  csextension <- as.factor(trimws(d[,"csextension"]))
  new.d <- data.frame(new.d, csextension)
  new.d <- apply_labels(new.d, csextension = "cs_extension")
temp.d <- data.frame (new.d.1, csextension)
summarytools::view(dfSummary(new.d$csextension, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	csextension [labelled, factor]	cs_extension	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	3 ( 0.2% ) 6 ( 0.4% ) 7 ( 0.4% ) 1052 ( 66.2% ) 26 ( 1.6% ) 52 ( 3.3% ) 32 ( 2.0% ) 57 ( 3.6% ) 23 ( 1.4% ) 245 ( 15.4% ) 9 ( 0.6% ) 5 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.1% ) 9 ( 0.6% ) 23 ( 1.4% ) 5 ( 0.3% ) 6 ( 0.4% ) 2 ( 0.1% ) 24 ( 1.5% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 64 ( 71.1% ) 3 ( 3.3% ) 5 ( 5.6% ) 2 ( 2.2% ) 3 ( 3.3% ) 1 ( 1.1% ) 5 ( 5.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.2% ) 1 ( 1.1% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 1 ( 1.1% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	1 ( 1.2% ) 0 ( 0.0% ) 1 ( 1.2% ) 57 ( 67.1% ) 1 ( 1.2% ) 9 ( 10.6% ) 6 ( 7.1% ) 1 ( 1.2% ) 2 ( 2.4% ) 5 ( 5.9% ) 1 ( 1.2% ) 0 ( 0.0% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	0 ( 0.0% ) 2 ( 1.4% ) 1 ( 0.7% ) 97 ( 69.8% ) 4 ( 2.9% ) 9 ( 6.5% ) 4 ( 2.9% ) 4 ( 2.9% ) 3 ( 2.2% ) 8 ( 5.8% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.9% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 33 ( 55.9% ) 1 ( 1.7% ) 1 ( 1.7% ) 3 ( 5.1% ) 4 ( 6.8% ) 2 ( 3.4% ) 12 ( 20.3% ) 0 ( 0.0% ) 1 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.7% ) 1 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	0 ( 0.0% ) 1 ( 0.9% ) 1 ( 0.9% ) 82 ( 71.3% ) 5 ( 4.3% ) 2 ( 1.7% ) 3 ( 2.6% ) 1 ( 0.9% ) 7 ( 6.1% ) 9 ( 7.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.9% ) 1 ( 0.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.9% ) 1 ( 0.9% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 709 ( 65.3% ) 12 ( 1.1% ) 26 ( 2.4% ) 14 ( 1.3% ) 44 ( 4.1% ) 8 ( 0.7% ) 200 ( 18.4% ) 7 ( 0.6% ) 4 ( 0.4% ) 0 ( 0.0% ) 2 ( 0.2% ) 6 ( 0.6% ) 17 ( 1.6% ) 3 ( 0.3% ) 4 ( 0.4% ) 1 ( 0.1% ) 21 ( 1.9% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_extension [factor]	1. 100 2. 130 3. 140 4. 150 5. 200 6. 210 7. 220 8. 230 9. 240 10. 300 11. 410 12. 420 13. 430 14. 440 15. 445 16. 450 17. 490 18. 500 19. 600 20. 999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 62.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 37.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS LYMPH NODES

• Description: Identifies the regional lymph nodes involved with cancer at the time of diagnosis.

• Rationale: The involvement of specific regional lymph nodes is a prognostic indicator used by Collaborative Staging to derive some TNM-N codes and SEER Summary Stage codes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Note: For cases prior to 2010, this was a 2 character field in CS version 1 which was converted to a 3 character field in CS version 2. Most 2 character codes were converted by adding a zero as the third character. For example, code 05 was usually converted to 050, 10 to 100, 11 to 110, etc. Special codes such as 88 and 99 were usually converted to 888 and 999 respectively.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2830

All data

st_css() #IMPORTANT!

  cslymphnodes <- as.factor(trimws(d[,"cslymphnodes"]))
  new.d <- data.frame(new.d, cslymphnodes)
  new.d <- apply_labels(new.d, cslymphnodes = "cs_lymph_nodes")
temp.d <- data.frame (new.d.1, cslymphnodes)
summarytools::view(dfSummary(new.d$cslymphnodes, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cslymphnodes [labelled, factor]	cs_lymph_nodes	1. 0 2. 100 3. 800 4. 999	1496 ( 94.1% ) 64 ( 4.0% ) 1 ( 0.1% ) 28 ( 1.8% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	83 ( 92.2% ) 7 ( 7.8% ) 0 ( 0.0% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	83 ( 97.6% ) 2 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	125 ( 89.9% ) 11 ( 7.9% ) 0 ( 0.0% ) 3 ( 2.2% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	57 ( 96.6% ) 2 ( 3.4% ) 0 ( 0.0% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	109 ( 94.8% ) 5 ( 4.3% ) 0 ( 0.0% ) 1 ( 0.9% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	1023 ( 94.3% ) 37 ( 3.4% ) 1 ( 0.1% ) 24 ( 2.2% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_lymph_nodes [factor]	1. 0 2. 100 3. 800 4. 999	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS METS AT DX

• Description: Identifies the distant site(s) of metastatic involvement at time of diagnosis.

• Rationale: The presence of metastatic disease at diagnosis is an independent prognostic indicator, and it is used by Collaborative Staging to derive TNM-M codes and SEER Summary Stage codes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2850

All data

st_css() #IMPORTANT!

  csmetsatdx <- as.factor(trimws(d[,"csmetsatdx"]))
  new.d <- data.frame(new.d, csmetsatdx)
  new.d <- apply_labels(new.d, csmetsatdx = "cs_mets_at_dx")
temp.d <- data.frame (new.d.1, csmetsatdx)
summarytools::view(dfSummary(new.d$csmetsatdx, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	csmetsatdx [labelled, factor]	cs_mets_at_dx	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	1531 ( 96.3% ) 1 ( 0.1% ) 6 ( 0.4% ) 24 ( 1.5% ) 4 ( 0.3% ) 2 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 19 ( 1.2% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	88 ( 97.8% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	83 ( 97.6% ) 1 ( 1.2% ) 0 ( 0.0% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	134 ( 96.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	56 ( 94.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 5.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	113 ( 98.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	1041 ( 95.9% ) 0 ( 0.0% ) 5 ( 0.5% ) 15 ( 1.4% ) 3 ( 0.3% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 17 ( 1.6% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_mets_at_dx [factor]	1. 0 2. 11 3. 12 4. 30 5. 35 6. 38 7. 40 8. 60 9. 99	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 7

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 7 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2861

All data

st_css() #IMPORTANT!

  cssitespecificfactor7 <- as.factor(trimws(d[,"cssitespecificfactor7"]))
  new.d <- data.frame(new.d, cssitespecificfactor7)
  new.d <- apply_labels(new.d, cssitespecificfactor7 = "cs_site_specific_factor7")
temp.d <- data.frame (new.d.1, cssitespecificfactor7)
summarytools::view(dfSummary(new.d$cssitespecificfactor7, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor7 [labelled, factor]	cs_site_specific_factor7	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	1 ( 0.0% ) 2 ( 0.1% ) 479 ( 22.5% ) 609 ( 28.6% ) 33 ( 1.5% ) 450 ( 21.1% ) 290 ( 13.6% ) 141 ( 6.6% ) 6 ( 0.3% ) 49 ( 2.3% ) 19 ( 0.9% ) 23 ( 1.1% ) 5 ( 0.2% ) 25 ( 1.2% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	0 ( 0.0% ) 0 ( 0.0% ) 57 ( 30.2% ) 54 ( 28.6% ) 3 ( 1.6% ) 35 ( 18.5% ) 12 ( 6.3% ) 13 ( 6.9% ) 0 ( 0.0% ) 4 ( 2.1% ) 0 ( 0.0% ) 6 ( 3.2% ) 1 ( 0.5% ) 4 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	0 ( 0.0% ) 0 ( 0.0% ) 62 ( 35.6% ) 59 ( 33.9% ) 2 ( 1.1% ) 29 ( 16.7% ) 9 ( 5.2% ) 7 ( 4.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	0 ( 0.0% ) 0 ( 0.0% ) 64 ( 27.0% ) 69 ( 29.1% ) 2 ( 0.8% ) 34 ( 14.3% ) 35 ( 14.8% ) 17 ( 7.2% ) 0 ( 0.0% ) 3 ( 1.3% ) 3 ( 1.3% ) 6 ( 2.5% ) 0 ( 0.0% ) 4 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	0 ( 0.0% ) 0 ( 0.0% ) 23 ( 16.2% ) 39 ( 27.5% ) 0 ( 0.0% ) 39 ( 27.5% ) 28 ( 19.7% ) 7 ( 4.9% ) 1 ( 0.7% ) 3 ( 2.1% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.7% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	0 ( 0.0% ) 0 ( 0.0% ) 45 ( 15.5% ) 76 ( 26.2% ) 12 ( 4.1% ) 68 ( 23.4% ) 51 ( 17.6% ) 22 ( 7.6% ) 0 ( 0.0% ) 9 ( 3.1% ) 4 ( 1.4% ) 3 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	1 ( 0.1% ) 2 ( 0.2% ) 222 ( 20.5% ) 307 ( 28.3% ) 14 ( 1.3% ) 242 ( 22.3% ) 154 ( 14.2% ) 75 ( 6.9% ) 5 ( 0.5% ) 28 ( 2.6% ) 10 ( 0.9% ) 6 ( 0.6% ) 3 ( 0.3% ) 15 ( 1.4% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor7 [factor]	1. 23 2. 32 3. 33 4. 34 5. 35 6. 43 7. 44 8. 45 9. 53 10. 54 11. 55 12. 99 13. 998 14. 999	0 ( 0.0% ) 0 ( 0.0% ) 6 ( 37.5% ) 5 ( 31.2% ) 0 ( 0.0% ) 3 ( 18.8% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 8

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 8 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2862

All data

st_css() #IMPORTANT!

  cssitespecificfactor8 <- as.factor(trimws(d[,"cssitespecificfactor8"]))
  new.d <- data.frame(new.d, cssitespecificfactor8)
  new.d <- apply_labels(new.d, cssitespecificfactor8 = "cs_site_specific_factor8")
temp.d <- data.frame (new.d.1, cssitespecificfactor8)
summarytools::view(dfSummary(new.d$cssitespecificfactor8, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor8 [labelled, factor]	cs_site_specific_factor8	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	21 ( 1.0% ) 3 ( 0.1% ) 488 ( 22.9% ) 1073 ( 50.3% ) 332 ( 15.6% ) 192 ( 9.0% ) 5 ( 0.2% ) 18 ( 0.8% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	0 ( 0.0% ) 0 ( 0.0% ) 59 ( 31.2% ) 92 ( 48.7% ) 16 ( 8.5% ) 18 ( 9.5% ) 1 ( 0.5% ) 3 ( 1.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	2 ( 1.1% ) 0 ( 0.0% ) 62 ( 35.6% ) 88 ( 50.6% ) 11 ( 6.3% ) 9 ( 5.2% ) 1 ( 0.6% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	4 ( 1.7% ) 0 ( 0.0% ) 66 ( 27.8% ) 104 ( 43.9% ) 38 ( 16.0% ) 21 ( 8.9% ) 0 ( 0.0% ) 4 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	0 ( 0.0% ) 0 ( 0.0% ) 23 ( 16.2% ) 79 ( 55.6% ) 29 ( 20.4% ) 10 ( 7.0% ) 0 ( 0.0% ) 1 ( 0.7% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	4 ( 1.4% ) 0 ( 0.0% ) 45 ( 15.5% ) 146 ( 50.3% ) 63 ( 21.7% ) 31 ( 10.7% ) 0 ( 0.0% ) 1 ( 0.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	11 ( 1.0% ) 3 ( 0.3% ) 226 ( 20.8% ) 556 ( 51.3% ) 174 ( 16.1% ) 103 ( 9.5% ) 3 ( 0.3% ) 8 ( 0.7% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor8 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	0 ( 0.0% ) 0 ( 0.0% ) 7 ( 43.8% ) 8 ( 50.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 9

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 9 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2863

All data

st_css() #IMPORTANT!

  cssitespecificfactor9 <- as.factor(trimws(d[,"cssitespecificfactor9"]))
  new.d <- data.frame(new.d, cssitespecificfactor9)
  new.d <- apply_labels(new.d, cssitespecificfactor9 = "cs_site_specific_factor9")
temp.d <- data.frame (new.d.1, cssitespecificfactor9)
summarytools::view(dfSummary(new.d$cssitespecificfactor9, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor9 [labelled, factor]	cs_site_specific_factor9	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	1 ( 0.0% ) 143 ( 6.7% ) 462 ( 21.7% ) 10 ( 0.5% ) 216 ( 10.1% ) 44 ( 2.1% ) 54 ( 2.5% ) 2 ( 0.1% ) 13 ( 0.6% ) 5 ( 0.2% ) 1 ( 0.0% ) 1159 ( 54.3% ) 23 ( 1.1% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	0 ( 0.0% ) 19 ( 10.1% ) 43 ( 22.8% ) 0 ( 0.0% ) 23 ( 12.2% ) 8 ( 4.2% ) 6 ( 3.2% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 85 ( 45.0% ) 3 ( 1.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	0 ( 0.0% ) 6 ( 3.4% ) 23 ( 13.2% ) 0 ( 0.0% ) 13 ( 7.5% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 129 ( 74.1% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	0 ( 0.0% ) 27 ( 11.4% ) 60 ( 25.3% ) 2 ( 0.8% ) 37 ( 15.6% ) 3 ( 1.3% ) 6 ( 2.5% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 99 ( 41.8% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	0 ( 0.0% ) 10 ( 7.0% ) 31 ( 21.8% ) 1 ( 0.7% ) 21 ( 14.8% ) 1 ( 0.7% ) 9 ( 6.3% ) 0 ( 0.0% ) 1 ( 0.7% ) 1 ( 0.7% ) 0 ( 0.0% ) 64 ( 45.1% ) 3 ( 2.1% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	0 ( 0.0% ) 26 ( 9.0% ) 92 ( 31.7% ) 3 ( 1.0% ) 29 ( 10.0% ) 15 ( 5.2% ) 9 ( 3.1% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 108 ( 37.2% ) 5 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	1 ( 0.1% ) 54 ( 5.0% ) 211 ( 19.4% ) 4 ( 0.4% ) 90 ( 8.3% ) 17 ( 1.6% ) 23 ( 2.1% ) 0 ( 0.0% ) 9 ( 0.8% ) 2 ( 0.2% ) 1 ( 0.1% ) 664 ( 61.2% ) 9 ( 0.8% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor9 [factor]	1. 32 2. 33 3. 34 4. 35 5. 43 6. 44 7. 45 8. 53 9. 54 10. 55 11. 99 12. 998 13. 999	0 ( 0.0% ) 1 ( 6.2% ) 2 ( 12.5% ) 0 ( 0.0% ) 3 ( 18.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 62.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 10

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor10 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2864

All data

st_css() #IMPORTANT!

  cssitespecificfactor10 <- as.factor(trimws(d[,"cssitespecificfactor10"]))
  new.d <- data.frame(new.d, cssitespecificfactor10)
  new.d <- apply_labels(new.d, cssitespecificfactor10 = "cs_site_specific_factor10")
temp.d <- data.frame (new.d.1, cssitespecificfactor10)
summarytools::view(dfSummary(new.d$cssitespecificfactor10, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor10 [labelled, factor]	cs_site_specific_factor10	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	5 ( 0.2% ) 1 ( 0.0% ) 145 ( 6.8% ) 682 ( 32.0% ) 56 ( 2.6% ) 67 ( 3.1% ) 1159 ( 54.3% ) 18 ( 0.8% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	0 ( 0.0% ) 0 ( 0.0% ) 19 ( 10.1% ) 66 ( 34.9% ) 8 ( 4.2% ) 8 ( 4.2% ) 85 ( 45.0% ) 3 ( 1.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	0 ( 0.0% ) 0 ( 0.0% ) 6 ( 3.4% ) 36 ( 20.7% ) 0 ( 0.0% ) 1 ( 0.6% ) 129 ( 74.1% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	1 ( 0.4% ) 0 ( 0.0% ) 27 ( 11.4% ) 97 ( 40.9% ) 6 ( 2.5% ) 6 ( 2.5% ) 99 ( 41.8% ) 1 ( 0.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	1 ( 0.7% ) 0 ( 0.0% ) 10 ( 7.0% ) 52 ( 36.6% ) 2 ( 1.4% ) 10 ( 7.0% ) 64 ( 45.1% ) 3 ( 2.1% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	1 ( 0.3% ) 0 ( 0.0% ) 26 ( 9.0% ) 121 ( 41.7% ) 19 ( 6.6% ) 10 ( 3.4% ) 108 ( 37.2% ) 5 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	2 ( 0.2% ) 1 ( 0.1% ) 56 ( 5.2% ) 305 ( 28.1% ) 21 ( 1.9% ) 32 ( 2.9% ) 664 ( 61.2% ) 4 ( 0.4% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor10 [factor]	1. 10 2. 5 3. 6 4. 7 5. 8 6. 9 7. 998 8. 999	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 62.5% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 11

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor11 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2865

All data

st_css() #IMPORTANT!

  cssitespecificfactor11 <- as.factor(trimws(d[,"cssitespecificfactor11"]))
  new.d <- data.frame(new.d, cssitespecificfactor11)
  new.d <- apply_labels(new.d, cssitespecificfactor11 = "cs_site_specific_factor11")
temp.d <- data.frame (new.d.1, cssitespecificfactor11)
summarytools::view(dfSummary(new.d$cssitespecificfactor11, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor11 [labelled, factor]	cs_site_specific_factor11	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	22 ( 1.0% ) 39 ( 1.8% ) 113 ( 5.3% ) 162 ( 7.6% ) 1129 ( 52.9% ) 668 ( 31.3% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	1 ( 0.5% ) 2 ( 1.1% ) 14 ( 7.4% ) 14 ( 7.4% ) 81 ( 42.9% ) 77 ( 40.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	0 ( 0.0% ) 3 ( 1.7% ) 9 ( 5.2% ) 3 ( 1.7% ) 129 ( 74.1% ) 30 ( 17.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	0 ( 0.0% ) 7 ( 3.0% ) 18 ( 7.6% ) 16 ( 6.8% ) 106 ( 44.7% ) 90 ( 38.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	3 ( 2.1% ) 1 ( 0.7% ) 8 ( 5.6% ) 45 ( 31.7% ) 43 ( 30.3% ) 42 ( 29.6% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	7 ( 2.4% ) 8 ( 2.8% ) 26 ( 9.0% ) 10 ( 3.4% ) 108 ( 37.2% ) 131 ( 45.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	11 ( 1.0% ) 18 ( 1.7% ) 38 ( 3.5% ) 71 ( 6.5% ) 654 ( 60.3% ) 293 ( 27.0% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor11 [factor]	1. 30 2. 40 3. 50 4. 988 5. 998 6. 999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 18.8% ) 8 ( 50.0% ) 5 ( 31.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 12

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor12 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2866

All data

st_css() #IMPORTANT!

  cssitespecificfactor12 <- as.factor(trimws(d[,"cssitespecificfactor12"]))
  new.d <- data.frame(new.d, cssitespecificfactor12)
  new.d <- apply_labels(new.d, cssitespecificfactor12 = "cs_site_specific_factor12")
temp.d <- data.frame (new.d.1, cssitespecificfactor12)
summarytools::view(dfSummary(new.d$cssitespecificfactor12, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor12 [labelled, factor]	cs_site_specific_factor12	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	4 ( 0.2% ) 218 ( 10.2% ) 77 ( 3.6% ) 66 ( 3.1% ) 76 ( 3.6% ) 12 ( 0.6% ) 13 ( 0.6% ) 6 ( 0.3% ) 6 ( 0.3% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 213 ( 10.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 2 ( 0.1% ) 216 ( 10.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 203 ( 9.5% ) 193 ( 9.1% ) 179 ( 8.4% ) 100 ( 4.7% ) 97 ( 4.5% ) 73 ( 3.4% ) 311 ( 14.6% ) 18 ( 0.8% ) 37 ( 1.7% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	0 ( 0.0% ) 21 ( 11.1% ) 2 ( 1.1% ) 5 ( 2.6% ) 3 ( 1.6% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 15 ( 7.9% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 25 ( 13.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 8.5% ) 11 ( 5.8% ) 11 ( 5.8% ) 9 ( 4.8% ) 11 ( 5.8% ) 7 ( 3.7% ) 38 ( 20.1% ) 3 ( 1.6% ) 4 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	1 ( 0.6% ) 27 ( 15.5% ) 6 ( 3.4% ) 2 ( 1.1% ) 6 ( 3.4% ) 1 ( 0.6% ) 1 ( 0.6% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 18 ( 10.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 21 ( 12.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 20 ( 11.5% ) 16 ( 9.2% ) 10 ( 5.7% ) 12 ( 6.9% ) 5 ( 2.9% ) 7 ( 4.0% ) 15 ( 8.6% ) 2 ( 1.1% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	1 ( 0.4% ) 21 ( 8.9% ) 14 ( 5.9% ) 14 ( 5.9% ) 7 ( 3.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 17 ( 7.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 6.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 25 ( 10.5% ) 21 ( 8.9% ) 25 ( 10.5% ) 10 ( 4.2% ) 11 ( 4.6% ) 7 ( 3.0% ) 39 ( 16.5% ) 2 ( 0.8% ) 2 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	0 ( 0.0% ) 15 ( 10.6% ) 6 ( 4.2% ) 3 ( 2.1% ) 4 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 14 ( 9.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 14 ( 9.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 6.3% ) 20 ( 14.1% ) 22 ( 15.5% ) 12 ( 8.5% ) 7 ( 4.9% ) 4 ( 2.8% ) 10 ( 7.0% ) 0 ( 0.0% ) 1 ( 0.7% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	1 ( 0.3% ) 22 ( 7.6% ) 10 ( 3.4% ) 11 ( 3.8% ) 7 ( 2.4% ) 3 ( 1.0% ) 3 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 28 ( 9.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 27 ( 9.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 27 ( 9.3% ) 30 ( 10.3% ) 33 ( 11.4% ) 13 ( 4.5% ) 18 ( 6.2% ) 4 ( 1.4% ) 46 ( 15.9% ) 3 ( 1.0% ) 3 ( 1.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	1 ( 0.1% ) 109 ( 10.1% ) 39 ( 3.6% ) 31 ( 2.9% ) 49 ( 4.5% ) 5 ( 0.5% ) 8 ( 0.7% ) 2 ( 0.2% ) 1 ( 0.1% ) 0 ( 0.0% ) 1 ( 0.1% ) 0 ( 0.0% ) 117 ( 10.8% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 113 ( 10.4% ) 1 ( 0.1% ) 1 ( 0.1% ) 106 ( 9.8% ) 95 ( 8.8% ) 77 ( 7.1% ) 43 ( 4.0% ) 45 ( 4.2% ) 42 ( 3.9% ) 158 ( 14.6% ) 8 ( 0.7% ) 26 ( 2.4% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor12 [factor]	1. 0 2. 1 3. 10 4. 11 5. 12 6. 13 7. 14 8. 15 9. 16 10. 17 11. 18 12. 19 13. 2 14. 20 15. 21 16. 23 17. 26 18. 3 19. 35 20. 38 21. 4 22. 5 23. 6 24. 7 25. 8 26. 9 27. 991 28. 998 29. 999	0 ( 0.0% ) 3 ( 18.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 2 ( 12.5% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 13

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor13 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2867

All data

st_css() #IMPORTANT!

  cssitespecificfactor13 <- as.factor(trimws(d[,"cssitespecificfactor13"]))
  new.d <- data.frame(new.d, cssitespecificfactor13)
  new.d <- apply_labels(new.d, cssitespecificfactor13 = "cs_site_specific_factor13")
temp.d <- data.frame (new.d.1, cssitespecificfactor13)
summarytools::view(dfSummary(new.d$cssitespecificfactor13, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor13 [labelled, factor]	cs_site_specific_factor13	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	3 ( 0.1% ) 34 ( 1.6% ) 22 ( 1.0% ) 994 ( 46.6% ) 65 ( 3.0% ) 172 ( 8.1% ) 49 ( 2.3% ) 58 ( 2.7% ) 24 ( 1.1% ) 30 ( 1.4% ) 20 ( 0.9% ) 7 ( 0.3% ) 8 ( 0.4% ) 9 ( 0.4% ) 6 ( 0.3% ) 3 ( 0.1% ) 5 ( 0.2% ) 1 ( 0.0% ) 3 ( 0.1% ) 7 ( 0.3% ) 4 ( 0.2% ) 2 ( 0.1% ) 6 ( 0.3% ) 1 ( 0.0% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 2 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 7 ( 0.3% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 1 ( 0.0% ) 16 ( 0.8% ) 61 ( 2.9% ) 12 ( 0.6% ) 21 ( 1.0% ) 8 ( 0.4% ) 399 ( 18.7% ) 18 ( 0.8% ) 36 ( 1.7% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	1 ( 0.5% ) 4 ( 2.1% ) 1 ( 0.5% ) 69 ( 36.5% ) 5 ( 2.6% ) 12 ( 6.3% ) 2 ( 1.1% ) 6 ( 3.2% ) 3 ( 1.6% ) 1 ( 0.5% ) 3 ( 1.6% ) 2 ( 1.1% ) 1 ( 0.5% ) 2 ( 1.1% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 8 ( 4.2% ) 0 ( 0.0% ) 3 ( 1.6% ) 1 ( 0.5% ) 52 ( 27.5% ) 3 ( 1.6% ) 4 ( 2.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	0 ( 0.0% ) 2 ( 1.1% ) 2 ( 1.1% ) 68 ( 39.1% ) 4 ( 2.3% ) 35 ( 20.1% ) 7 ( 4.0% ) 10 ( 5.7% ) 6 ( 3.4% ) 5 ( 2.9% ) 2 ( 1.1% ) 0 ( 0.0% ) 3 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 4 ( 2.3% ) 2 ( 1.1% ) 1 ( 0.6% ) 1 ( 0.6% ) 15 ( 8.6% ) 2 ( 1.1% ) 1 ( 0.6% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	0 ( 0.0% ) 5 ( 2.1% ) 3 ( 1.3% ) 106 ( 44.7% ) 6 ( 2.5% ) 21 ( 8.9% ) 9 ( 3.8% ) 8 ( 3.4% ) 3 ( 1.3% ) 4 ( 1.7% ) 2 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 6 ( 2.5% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 56 ( 23.6% ) 2 ( 0.8% ) 2 ( 0.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	0 ( 0.0% ) 2 ( 1.4% ) 5 ( 3.5% ) 70 ( 49.3% ) 11 ( 7.7% ) 8 ( 5.6% ) 2 ( 1.4% ) 4 ( 2.8% ) 0 ( 0.0% ) 2 ( 1.4% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 32 ( 22.5% ) 0 ( 0.0% ) 2 ( 1.4% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	0 ( 0.0% ) 5 ( 1.7% ) 2 ( 0.7% ) 101 ( 34.8% ) 2 ( 0.7% ) 47 ( 16.2% ) 4 ( 1.4% ) 3 ( 1.0% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 12 ( 4.1% ) 5 ( 1.7% ) 7 ( 2.4% ) 4 ( 1.4% ) 83 ( 28.6% ) 3 ( 1.0% ) 3 ( 1.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	2 ( 0.2% ) 16 ( 1.5% ) 9 ( 0.8% ) 575 ( 53.0% ) 37 ( 3.4% ) 49 ( 4.5% ) 25 ( 2.3% ) 27 ( 2.5% ) 10 ( 0.9% ) 16 ( 1.5% ) 11 ( 1.0% ) 5 ( 0.5% ) 4 ( 0.4% ) 6 ( 0.6% ) 4 ( 0.4% ) 2 ( 0.2% ) 4 ( 0.4% ) 0 ( 0.0% ) 3 ( 0.3% ) 7 ( 0.6% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 6 ( 0.6% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 12 ( 1.1% ) 31 ( 2.9% ) 4 ( 0.4% ) 10 ( 0.9% ) 1 ( 0.1% ) 150 ( 13.8% ) 8 ( 0.7% ) 24 ( 2.2% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor13 [factor]	1. 1 2. 10 3. 11 4. 12 5. 13 6. 14 7. 15 8. 16 9. 17 10. 18 11. 19 12. 2 13. 20 14. 21 15. 22 16. 23 17. 24 18. 25 19. 26 20. 27 21. 28 22. 29 23. 3 24. 30 25. 31 26. 32 27. 33 28. 34 29. 35 30. 36 31. 37 32. 38 33. 4 34. 40 35. 41 36. 42 37. 43 38. 47 39. 48 40. 5 41. 6 42. 7 43. 8 44. 9 45. 991 46. 998 47. 999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 68.8% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 14

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor14 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2868

All data

st_css() #IMPORTANT!

  cssitespecificfactor14 <- as.factor(trimws(d[,"cssitespecificfactor14"]))
  new.d <- data.frame(new.d, cssitespecificfactor14)
  new.d <- apply_labels(new.d, cssitespecificfactor14 = "cs_site_specific_factor14")
temp.d <- data.frame (new.d.1, cssitespecificfactor14)
summarytools::view(dfSummary(new.d$cssitespecificfactor14, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor14 [labelled, factor]	cs_site_specific_factor14	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	2 ( 0.1% ) 489 ( 22.9% ) 707 ( 33.2% ) 105 ( 4.9% ) 2 ( 0.1% ) 745 ( 34.9% ) 18 ( 0.8% ) 64 ( 3.0% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	0 ( 0.0% ) 58 ( 30.7% ) 82 ( 43.4% ) 15 ( 7.9% ) 0 ( 0.0% ) 32 ( 16.9% ) 1 ( 0.5% ) 1 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	1 ( 0.6% ) 76 ( 43.7% ) 77 ( 44.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 17 ( 9.8% ) 3 ( 1.7% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	1 ( 0.4% ) 78 ( 32.9% ) 112 ( 47.3% ) 18 ( 7.6% ) 2 ( 0.8% ) 20 ( 8.4% ) 2 ( 0.8% ) 4 ( 1.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	0 ( 0.0% ) 7 ( 4.9% ) 18 ( 12.7% ) 7 ( 4.9% ) 0 ( 0.0% ) 107 ( 75.4% ) 2 ( 1.4% ) 1 ( 0.7% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	0 ( 0.0% ) 81 ( 27.9% ) 128 ( 44.1% ) 18 ( 6.2% ) 0 ( 0.0% ) 47 ( 16.2% ) 4 ( 1.4% ) 12 ( 4.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	0 ( 0.0% ) 186 ( 17.2% ) 288 ( 26.6% ) 47 ( 4.3% ) 0 ( 0.0% ) 511 ( 47.1% ) 6 ( 0.6% ) 46 ( 4.2% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor14 [factor]	1. 0 2. 10 3. 20 4. 30 5. 50 6. 988 7. 998 8. 999	0 ( 0.0% ) 3 ( 18.8% ) 2 ( 12.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 68.8% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 15

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor15 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2869

All data

st_css() #IMPORTANT!

  cssitespecificfactor15 <- as.factor(trimws(d[,"cssitespecificfactor15"]))
  new.d <- data.frame(new.d, cssitespecificfactor15)
  new.d <- apply_labels(new.d, cssitespecificfactor15 = "cs_site_specific_factor15")
temp.d <- data.frame (new.d.1, cssitespecificfactor15)
summarytools::view(dfSummary(new.d$cssitespecificfactor15, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor15 [labelled, factor]	cs_site_specific_factor15	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	30 ( 1.4% ) 167 ( 7.8% ) 177 ( 8.3% ) 734 ( 34.4% ) 752 ( 35.3% ) 272 ( 12.8% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	3 ( 1.6% ) 14 ( 7.4% ) 13 ( 6.9% ) 105 ( 55.6% ) 31 ( 16.4% ) 23 ( 12.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	2 ( 1.1% ) 33 ( 19.0% ) 18 ( 10.3% ) 99 ( 56.9% ) 17 ( 9.8% ) 5 ( 2.9% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	4 ( 1.7% ) 24 ( 10.1% ) 24 ( 10.1% ) 144 ( 60.8% ) 21 ( 8.9% ) 20 ( 8.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	0 ( 0.0% ) 4 ( 2.8% ) 2 ( 1.4% ) 13 ( 9.2% ) 112 ( 78.9% ) 11 ( 7.7% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	9 ( 3.1% ) 26 ( 9.0% ) 26 ( 9.0% ) 145 ( 50.0% ) 50 ( 17.2% ) 34 ( 11.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	12 ( 1.1% ) 66 ( 6.1% ) 94 ( 8.7% ) 225 ( 20.8% ) 509 ( 47.0% ) 178 ( 16.4% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor15 [factor]	1. 0 2. 10 3. 20 4. 30 5. 988 6. 999	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 18.8% ) 12 ( 75.0% ) 1 ( 6.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 1

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 1 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2880

All data

st_css() #IMPORTANT!

  cssitespecificfactor1 <- as.factor(trimws(d[,"cssitespecificfactor1"]))
  new.d <- data.frame(new.d, cssitespecificfactor1)
  new.d <- apply_labels(new.d, cssitespecificfactor1 = "cs_site_specific_factor1")
temp.d <- data.frame (new.d.1, cssitespecificfactor1)
summarytools::view(dfSummary(new.d$cssitespecificfactor1, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor1 [labelled, factor]	cs_site_specific_factor1	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	3 ( 0.1% ) 2 ( 0.1% ) 14 ( 0.7% ) 9 ( 0.4% ) 8 ( 0.4% ) 10 ( 0.5% ) 5 ( 0.2% ) 12 ( 0.6% ) 8 ( 0.4% ) 5 ( 0.2% ) 2 ( 0.1% ) 4 ( 0.2% ) 2 ( 0.1% ) 6 ( 0.3% ) 7 ( 0.3% ) 6 ( 0.3% ) 5 ( 0.2% ) 6 ( 0.3% ) 6 ( 0.3% ) 4 ( 0.2% ) 2 ( 0.1% ) 4 ( 0.2% ) 6 ( 0.3% ) 11 ( 0.5% ) 6 ( 0.3% ) 5 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 7 ( 0.3% ) 2 ( 0.1% ) 7 ( 0.3% ) 7 ( 0.3% ) 6 ( 0.3% ) 2 ( 0.1% ) 6 ( 0.3% ) 2 ( 0.1% ) 3 ( 0.1% ) 7 ( 0.3% ) 2 ( 0.1% ) 1 ( 0.0% ) 6 ( 0.3% ) 4 ( 0.2% ) 5 ( 0.2% ) 2 ( 0.1% ) 2 ( 0.1% ) 4 ( 0.2% ) 3 ( 0.1% ) 2 ( 0.1% ) 2 ( 0.1% ) 3 ( 0.1% ) 1885 ( 88.4% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	2 ( 1.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 3 ( 1.6% ) 1 ( 0.5% ) 2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 161 ( 85.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 3 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 155 ( 89.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.8% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.8% ) 2 ( 0.8% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 209 ( 88.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.7% ) 1 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.7% ) 1 ( 0.7% ) 1 ( 0.7% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 131 ( 92.3% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 261 ( 90.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	1 ( 0.1% ) 1 ( 0.1% ) 9 ( 0.8% ) 4 ( 0.4% ) 4 ( 0.4% ) 5 ( 0.5% ) 2 ( 0.2% ) 8 ( 0.7% ) 5 ( 0.5% ) 2 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.2% ) 0 ( 0.0% ) 5 ( 0.5% ) 1 ( 0.1% ) 4 ( 0.4% ) 0 ( 0.0% ) 2 ( 0.2% ) 4 ( 0.4% ) 3 ( 0.3% ) 0 ( 0.0% ) 3 ( 0.3% ) 4 ( 0.4% ) 8 ( 0.7% ) 3 ( 0.3% ) 3 ( 0.3% ) 1 ( 0.1% ) 2 ( 0.2% ) 4 ( 0.4% ) 2 ( 0.2% ) 5 ( 0.5% ) 4 ( 0.4% ) 4 ( 0.4% ) 2 ( 0.2% ) 2 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.1% ) 3 ( 0.3% ) 2 ( 0.2% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 954 ( 88.0% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor1 [factor]	1. 1 2. 10 3. 100 4. 101 5. 102 6. 103 7. 104 8. 105 9. 106 10. 107 11. 108 12. 109 13. 11 14. 110 15. 111 16. 112 17. 113 18. 114 19. 115 20. 116 21. 117 22. 118 23. 119 24. 120 25. 121 26. 122 27. 123 28. 124 29. 125 30. 126 31. 127 32. 128 33. 129 34. 13 35. 130 36. 131 37. 132 38. 133 39. 134 40. 135 41. 136 42. 137 43. 138 44. 139 45. 14 46. 140 47. 141 48. 142 49. 143 50. 144 [ 308 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 14 ( 87.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 2

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 2 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2890

All data

st_css() #IMPORTANT!

  cssitespecificfactor2 <- as.factor(trimws(d[,"cssitespecificfactor2"]))
  new.d <- data.frame(new.d, cssitespecificfactor2)
  new.d <- apply_labels(new.d, cssitespecificfactor2 = "cs_site_specific_factor2")
temp.d <- data.frame (new.d.1, cssitespecificfactor2)
summarytools::view(dfSummary(new.d$cssitespecificfactor2, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor2 [labelled, factor]	cs_site_specific_factor2	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	1989 ( 93.3% ) 54 ( 2.5% ) 5 ( 0.2% ) 9 ( 0.4% ) 7 ( 0.3% ) 68 ( 3.2% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	173 ( 91.5% ) 9 ( 4.8% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 3.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	162 ( 93.1% ) 7 ( 4.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 2 ( 1.1% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	217 ( 91.6% ) 7 ( 3.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 2 ( 0.8% ) 10 ( 4.2% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	130 ( 91.5% ) 4 ( 2.8% ) 0 ( 0.0% ) 3 ( 2.1% ) 0 ( 0.0% ) 5 ( 3.5% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	278 ( 95.9% ) 7 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 4 ( 1.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	1016 ( 93.7% ) 20 ( 1.8% ) 3 ( 0.3% ) 3 ( 0.3% ) 3 ( 0.3% ) 39 ( 3.6% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor2 [factor]	1. 10 2. 20 3. 30 4. 997 5. 998 6. 999	13 ( 81.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 2 ( 12.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 3

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 3 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2900

All data

st_css() #IMPORTANT!

  cssitespecificfactor3 <- as.factor(trimws(d[,"cssitespecificfactor3"]))
  new.d <- data.frame(new.d, cssitespecificfactor3)
  new.d <- apply_labels(new.d, cssitespecificfactor3 = "cs_site_specific_factor3")
temp.d <- data.frame (new.d.1, cssitespecificfactor3)
summarytools::view(dfSummary(new.d$cssitespecificfactor3, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor3 [labelled, factor]	cs_site_specific_factor3	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	1 ( 0.0% ) 5 ( 0.2% ) 45 ( 2.1% ) 11 ( 0.5% ) 499 ( 23.4% ) 40 ( 1.9% ) 2 ( 0.1% ) 2 ( 0.1% ) 1 ( 0.0% ) 11 ( 0.5% ) 6 ( 0.3% ) 1 ( 0.0% ) 1 ( 0.0% ) 51 ( 2.4% ) 41 ( 1.9% ) 54 ( 2.5% ) 9 ( 0.4% ) 34 ( 1.6% ) 20 ( 0.9% ) 11 ( 0.5% ) 100 ( 4.7% ) 11 ( 0.5% ) 2 ( 0.1% ) 3 ( 0.1% ) 2 ( 0.1% ) 25 ( 1.2% ) 1134 ( 53.2% ) 5 ( 0.2% ) 6 ( 0.3% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	0 ( 0.0% ) 1 ( 0.5% ) 4 ( 2.1% ) 3 ( 1.6% ) 53 ( 28.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 0 ( 0.0% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 6 ( 3.2% ) 6 ( 3.2% ) 7 ( 3.7% ) 1 ( 0.5% ) 3 ( 1.6% ) 1 ( 0.5% ) 0 ( 0.0% ) 11 ( 5.8% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 83 ( 43.9% ) 1 ( 0.5% ) 1 ( 0.5% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	0 ( 0.0% ) 0 ( 0.0% ) 5 ( 2.9% ) 0 ( 0.0% ) 14 ( 8.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.7% ) 4 ( 2.3% ) 5 ( 2.9% ) 1 ( 0.6% ) 3 ( 1.7% ) 3 ( 1.7% ) 0 ( 0.0% ) 4 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 129 ( 74.1% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	0 ( 0.0% ) 3 ( 1.3% ) 5 ( 2.1% ) 1 ( 0.4% ) 73 ( 30.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.3% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 12 ( 5.1% ) 9 ( 3.8% ) 7 ( 3.0% ) 2 ( 0.8% ) 6 ( 2.5% ) 2 ( 0.8% ) 0 ( 0.0% ) 10 ( 4.2% ) 3 ( 1.3% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.3% ) 96 ( 40.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	0 ( 0.0% ) 0 ( 0.0% ) 3 ( 2.1% ) 1 ( 0.7% ) 33 ( 23.2% ) 3 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 4.2% ) 1 ( 0.7% ) 10 ( 7.0% ) 0 ( 0.0% ) 4 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 12 ( 8.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 66 ( 46.5% ) 0 ( 0.0% ) 0 ( 0.0% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	0 ( 0.0% ) 0 ( 0.0% ) 9 ( 3.1% ) 1 ( 0.3% ) 87 ( 30.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 2 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 13 ( 4.5% ) 10 ( 3.4% ) 9 ( 3.1% ) 5 ( 1.7% ) 9 ( 3.1% ) 3 ( 1.0% ) 3 ( 1.0% ) 19 ( 6.6% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 0 ( 0.0% ) 6 ( 2.1% ) 104 ( 35.9% ) 2 ( 0.7% ) 1 ( 0.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	1 ( 0.1% ) 1 ( 0.1% ) 19 ( 1.8% ) 5 ( 0.5% ) 235 ( 21.7% ) 35 ( 3.2% ) 1 ( 0.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 0.3% ) 2 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 1.0% ) 11 ( 1.0% ) 16 ( 1.5% ) 0 ( 0.0% ) 9 ( 0.8% ) 10 ( 0.9% ) 8 ( 0.7% ) 44 ( 4.1% ) 4 ( 0.4% ) 0 ( 0.0% ) 2 ( 0.2% ) 1 ( 0.1% ) 15 ( 1.4% ) 646 ( 59.5% ) 2 ( 0.2% ) 4 ( 0.4% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor3 [factor]	1. 0 2. 200 3. 210 4. 220 5. 230 6. 300 7. 320 8. 330 9. 340 10. 350 11. 400 12. 402 13. 404 14. 406 15. 415 16. 420 17. 430 18. 480 19. 482 20. 483 21. 485 22. 490 23. 495 24. 500 25. 950 26. 960 27. 970 28. 980 29. 990	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 10 ( 62.5% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 4

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 4 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2910

All data

st_css() #IMPORTANT!

  cssitespecificfactor4 <- as.factor(trimws(d[,"cssitespecificfactor4"]))
  new.d <- data.frame(new.d, cssitespecificfactor4)
  new.d <- apply_labels(new.d, cssitespecificfactor4 = "cs_site_specific_factor4")
temp.d <- data.frame (new.d.1, cssitespecificfactor4)
summarytools::view(dfSummary(new.d$cssitespecificfactor4, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor4 [labelled, factor]	cs_site_specific_factor4	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	19 ( 0.9% ) 1 ( 0.0% ) 3 ( 0.1% ) 38 ( 1.8% ) 9 ( 0.4% ) 10 ( 0.5% ) 1 ( 0.0% ) 1 ( 0.0% ) 73 ( 3.4% ) 1 ( 0.0% ) 1 ( 0.0% ) 3 ( 0.1% ) 1 ( 0.0% ) 3 ( 0.1% ) 11 ( 0.5% ) 1 ( 0.0% ) 2 ( 0.1% ) 1 ( 0.0% ) 278 ( 13.0% ) 1675 ( 78.6% )		35 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.1% ) 2 ( 1.1% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 1.6% ) 1 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 1 ( 0.5% ) 0 ( 0.0% ) 9 ( 4.8% ) 167 ( 88.4% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 9 ( 5.2% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 5.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 8 ( 4.6% ) 145 ( 83.3% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 2 ( 0.8% ) 3 ( 1.3% ) 2 ( 0.8% ) 0 ( 0.0% ) 1 ( 0.4% ) 4 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 21 ( 8.9% ) 201 ( 84.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	7 ( 4.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 19 ( 13.4% ) 113 ( 79.6% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	2 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.3% ) 4 ( 1.4% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.3% ) 0 ( 0.0% ) 23 ( 7.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 23 ( 7.9% ) 231 ( 79.7% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	8 ( 0.7% ) 1 ( 0.1% ) 0 ( 0.0% ) 21 ( 1.9% ) 0 ( 0.0% ) 4 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 32 ( 3.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 9 ( 0.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.1% ) 197 ( 18.2% ) 803 ( 74.1% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor4 [factor]	1. 110 2. 120 3. 140 4. 150 5. 210 6. 220 7. 230 8. 240 9. 250 10. 310 11. 330 12. 350 13. 430 14. 440 15. 450 16. 510 17. 520 18. 540 19. 550 20. 988	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 15 ( 93.8% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 5

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 5 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2920

All data

st_css() #IMPORTANT!

  cssitespecificfactor5 <- as.factor(trimws(d[,"cssitespecificfactor5"]))
  new.d <- data.frame(new.d, cssitespecificfactor5)
  new.d <- apply_labels(new.d, cssitespecificfactor5 = "cs_site_specific_factor5")
temp.d <- data.frame (new.d.1, cssitespecificfactor5)
summarytools::view(dfSummary(new.d$cssitespecificfactor5, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor5 [labelled, factor]	cs_site_specific_factor5	1. 988	2133 ( 100.0% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	142 ( 100.0% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	1085 ( 100.0% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor5 [factor]	1. 988	16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

CS SITE-SPECIFIC FACTOR 6

• Description: Identifies additional information needed to generate stage, or prognostic factors that have an effect on stage or survival.

• Rationale: Site-specific factors are used to record additional staging information needed by Collaborative Staging to derive TNM and/or SEER Summary Stage codes for particular site-histology schema.

• Codes (The information recorded in CS Site-Specific Factor 6 differs for each anatomic site. See the most current version of the Collaborative Stage Data Collection System (http://cancerstaging.org),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2930

All data

st_css() #IMPORTANT!

  cssitespecificfactor6 <- as.factor(trimws(d[,"cssitespecificfactor6"]))
  new.d <- data.frame(new.d, cssitespecificfactor6)
  new.d <- apply_labels(new.d, cssitespecificfactor6 = "cs_site_specific_factor6")
temp.d <- data.frame (new.d.1, cssitespecificfactor6)
summarytools::view(dfSummary(new.d$cssitespecificfactor6, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cssitespecificfactor6 [labelled, factor]	cs_site_specific_factor6	1. 988	2133 ( 100.0% )		34 (1.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	189 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	174 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	237 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	142 ( 100.0% )		32 (18.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	290 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	1085 ( 100.0% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	cs_site_specific_factor6 [factor]	1. 988	16 ( 100.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-6 T

• Description: This data item belongs to the Collaborative Stage (CS) Data Collection System which is based on the AJCC Cancer Staging Manual, 6th and 7th editions. AJCC T, N, M plus descriptors and AJCC staging components are composed of combinations of characters, numbers, and/or special characters and can be of varying lengths. To more easily handle these components a numeric code was assigned to each unique category for each T, N, M plus descriptors and AJCC stage for 6th and 7th editions. This field contains the numeric representation for the AJCC 6th edition “T” and is derived from CS coded fields using the CS algorithm. This numeric representation is referred to as the “storage” code and its associated label is referred to as the “display” code. Explanations of the “storage” codes and their corresponding “display” codes can be found in the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx).13 The display code should be used for display on the screen and in reports.

• Rationale: The Collaborative Stage Data Collection System was designed by a joint task force including representatives from SEER, ACoS, CDC, NAACCR, NCRA, CCCR, CPAC, and AJCC, to provide a single uniform set of codes and rules for coding extent of disease (EOD) and stage information to meet the needs of all of the participating standard setters. When CS data items are coded, a computer algorithm provides the derivation of T, N, M, and stage-based on AJCC Cancer Staging Manual 6th & 7th Editions, SEER Summary Stage 1977, and SEER Summary Stage 2000. There are separate derived CS fields in the NAACCR record based on AJCC 6th Edition for 2004+ cases and AJCC 7th Edition for 2010+ cases.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2940

All data

st_css() #IMPORTANT!

  derivedajcc6t <- as.factor(trimws(d[,"derivedajcc6t"]))
  new.d <- data.frame(new.d, derivedajcc6t)
  new.d <- apply_labels(new.d, derivedajcc6t = "derived_ajcc_6t")
temp.d <- data.frame (new.d.1, derivedajcc6t)
summarytools::view(dfSummary(new.d$derivedajcc6t, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc6t [labelled, factor]	derived_ajcc_6t	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	5 ( 0.3% ) 7 ( 0.4% ) 608 ( 38.3% ) 2 ( 0.1% ) 64 ( 4.0% ) 25 ( 1.6% ) 440 ( 27.7% ) 199 ( 12.5% ) 99 ( 6.2% ) 80 ( 5.0% ) 10 ( 0.6% ) 30 ( 1.9% ) 20 ( 1.3% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	0 ( 0.0% ) 0 ( 0.0% ) 20 ( 22.2% ) 0 ( 0.0% ) 5 ( 5.6% ) 5 ( 5.6% ) 38 ( 42.2% ) 1 ( 1.1% ) 13 ( 14.4% ) 6 ( 6.7% ) 0 ( 0.0% ) 2 ( 2.2% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	0 ( 0.0% ) 1 ( 1.2% ) 45 ( 52.9% ) 1 ( 1.2% ) 8 ( 9.4% ) 3 ( 3.5% ) 11 ( 12.9% ) 7 ( 8.2% ) 7 ( 8.2% ) 1 ( 1.2% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	2 ( 1.4% ) 1 ( 0.7% ) 48 ( 34.5% ) 0 ( 0.0% ) 7 ( 5.0% ) 2 ( 1.4% ) 47 ( 33.8% ) 8 ( 5.8% ) 12 ( 8.6% ) 9 ( 6.5% ) 1 ( 0.7% ) 1 ( 0.7% ) 1 ( 0.7% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	0 ( 0.0% ) 0 ( 0.0% ) 10 ( 16.9% ) 0 ( 0.0% ) 2 ( 3.4% ) 1 ( 1.7% ) 28 ( 47.5% ) 6 ( 10.2% ) 6 ( 10.2% ) 4 ( 6.8% ) 1 ( 1.7% ) 1 ( 1.7% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	1 ( 0.9% ) 1 ( 0.9% ) 27 ( 23.5% ) 0 ( 0.0% ) 7 ( 6.1% ) 2 ( 1.7% ) 46 ( 40.0% ) 12 ( 10.4% ) 10 ( 8.7% ) 5 ( 4.3% ) 0 ( 0.0% ) 4 ( 3.5% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	2 ( 0.2% ) 4 ( 0.4% ) 453 ( 41.8% ) 1 ( 0.1% ) 35 ( 3.2% ) 12 ( 1.1% ) 265 ( 24.4% ) 160 ( 14.7% ) 51 ( 4.7% ) 55 ( 5.1% ) 7 ( 0.6% ) 21 ( 1.9% ) 19 ( 1.8% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6t [factor]	1. 12 2. 15 3. 18 4. 19 5. 21 6. 22 7. 23 8. 29 9. 31 10. 32 11. 39 12. 40 13. 99	0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-6 N

• Description: This data item belongs to the Collaborative Stage (CS) Data Collection System which is based on the AJCC Cancer Staging Manual, 6th and 7th editions. AJCC T, N, M plus descriptors and AJCC staging components are composed of combinations of characters, numbers, and/or special characters and can be of varying lengths. To more easily handle these components a numeric code was assigned to each unique category for each T, N, M plus descriptors and AJCC stage for 6th and 7th editions. This field contains the numeric representation for AJCC 6th edition “N” and is derived from CS coded fields using the CS algorithm. This numeric representation is referred to as the “storage” code and its associated label is referred to as the “display” code. Explanations of the “storage” codes and their corresponding “display” codes can be found in the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx).13 The display code should be used for display on the screen and in reports.

• Rationale: The Collaborative Stage Data Collection System was designed by a joint task force including representatives from SEER, ACoS, CDC, NAACCR, NCRA, CCCR, CPAC, and AJCC, to provide a single uniform set of codes and rules for coding extent of disease (EOD) and stage information to meet the needs of all of the participating standard setters. When CS data items are coded, a computer algorithm provides the derivation of T, N, M, and stage-based on AJCC Cancer Staging Manual 6th & 7th Editions, SEER Summary Stage 1977, and SEER Summary Stage 2000. There are separate derived CS fields in the NAACCR record based on AJCC 6th Edition for 2004+ cases and AJCC 7th Edition for 2010+ cases.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2960

All data

st_css() #IMPORTANT!

  derivedajcc6n <- as.factor(trimws(d[,"derivedajcc6n"]))
  new.d <- data.frame(new.d, derivedajcc6n)
  new.d <- apply_labels(new.d, derivedajcc6n = "derived_ajcc_6n")
temp.d <- data.frame (new.d.1, derivedajcc6n)
summarytools::view(dfSummary(new.d$derivedajcc6n, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc6n [labelled, factor]	derived_ajcc_6n	1. 0 2. 10 3. 99	1496 ( 94.1% ) 65 ( 4.1% ) 28 ( 1.8% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	83 ( 92.2% ) 7 ( 7.8% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	83 ( 97.6% ) 2 ( 2.4% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	125 ( 89.9% ) 11 ( 7.9% ) 3 ( 2.2% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	57 ( 96.6% ) 2 ( 3.4% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	109 ( 94.8% ) 5 ( 4.3% ) 1 ( 0.9% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	1023 ( 94.3% ) 38 ( 3.5% ) 24 ( 2.2% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6n [factor]	1. 0 2. 10 3. 99	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-6 M

• Description: This data item belongs to the Collaborative Stage (CS) Data Collection System which is based on the AJCC Cancer Staging Manual, 6th and 7th editions. AJCC T, N, M plus descriptors and AJCC staging components are composed of combinations of characters, numbers, and/or special characters and can be of varying lengths. To more easily handle these components a numeric code was assigned to each unique category for each T, N, M plus descriptors and AJCC stage for 6th and 7th editions. This field contains the numeric representation for AJCC 6th edition “M” and is derived from CS coded fields using the CS algorithm. This numeric representation is referred to as the “storage” code and its associated label is referred to as the “display” code. Explanations of the “storage” codes and their corresponding “display” codes can be found in the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx).13 The display code should be used for display on the screen and in reports.

• Rationale: The Collaborative Stage Data Collection System was designed by a joint task force including representatives from SEER, ACoS, CDC, NAACCR, NCRA, CCCR, CPAC, and AJCC, to provide a single uniform set of codes and rules for coding extent of disease (EOD) and stage information to meet the needs of all of the participating standard setters. When CS data items are coded, a computer algorithm provides the derivation of T, N, M, and stage-based on AJCC Cancer Staging Manual 6th & 7th Editions, SEER Summary Stage 1977, and SEER Summary Stage 2000. There are separate derived CS fields in the NAACCR record based on AJCC 6th Edition for 2004+ cases and AJCC 7th Edition for 2010+ cases.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#2980

All data

st_css() #IMPORTANT!

  derivedajcc6m <- as.factor(trimws(d[,"derivedajcc6m"]))
  new.d <- data.frame(new.d, derivedajcc6m)
  new.d <- apply_labels(new.d, derivedajcc6m = "derived_ajcc_6m")
temp.d <- data.frame (new.d.1, derivedajcc6m)
summarytools::view(dfSummary(new.d$derivedajcc6m, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc6m [labelled, factor]	derived_ajcc_6m	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	1531 ( 96.3% ) 7 ( 0.4% ) 30 ( 1.9% ) 1 ( 0.1% ) 1 ( 0.1% ) 19 ( 1.2% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	88 ( 97.8% ) 1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	83 ( 97.6% ) 1 ( 1.2% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	134 ( 96.4% ) 0 ( 0.0% ) 3 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	56 ( 94.9% ) 0 ( 0.0% ) 3 ( 5.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	113 ( 98.3% ) 0 ( 0.0% ) 2 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	1041 ( 95.9% ) 5 ( 0.5% ) 20 ( 1.8% ) 1 ( 0.1% ) 1 ( 0.1% ) 17 ( 1.6% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6m [factor]	1. 0 2. 11 3. 12 4. 13 5. 19 6. 99	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-6 STAGE GRP

• Description: This data item belongs to the Collaborative Stage (CS) Data Collection System which is based on the AJCC Cancer Staging Manual, 6th and 7th editions. AJCC T, N, M plus descriptors and AJCC staging components are composed of combinations of characters, numbers, and/or special characters and can be of varying lengths. To more easily handle these components a numeric code was assigned to each unique category for each T, N, M plus descriptors and AJCC stage for 6th and 7th editions. This field contains the numeric representation for the AJCC 6th edition “Stage Group” and is derived from CS coded fields using the CS algorithm. This numeric representation is referred to as the “storage” code and its associated label is referred to as the “display” code. Explanations of the “storage” codes and their corresponding “display” codes can be found in the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx).13 The display code should be used for display on the screen and in reports.

• Rationale: The Collaborative Stage Data Collection System was designed by a joint task force including representatives from SEER, ACoS, CDC, NAACCR, NCRA, CCCR, CPAC, and AJCC, to provide a single uniform set of codes and rules for coding extent of disease (EOD) and stage information to meet the needs of all of the participating standard setters. When CS data items are coded, a computer algorithm provides the derivation of T, N, M, and stage-based on AJCC Cancer Staging Manual 6th & 7th Editions, SEER Summary Stage 1977, and SEER Summary Stage 2000. There are separate derived CS fields in the NAACCR record based on AJCC 6th Edition for 2004+ cases and AJCC 7th Edition for 2010+ cases.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3000

All data

st_css() #IMPORTANT!

  derivedajcc6stagegrp <- as.factor(trimws(d[,"derivedajcc6stagegrp"]))
  new.d <- data.frame(new.d, derivedajcc6stagegrp)
  new.d <- apply_labels(new.d, derivedajcc6stagegrp = "derived_ajcc_6_stage_grp")
temp.d <- data.frame (new.d.1, derivedajcc6stagegrp)
summarytools::view(dfSummary(new.d$derivedajcc6stagegrp, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc6stagegrp [labelled, factor]	derived_ajcc_6_stage_grp	1. 10 2. 30 3. 50 4. 70 5. 99	4 ( 0.3% ) 1281 ( 80.6% ) 155 ( 9.8% ) 112 ( 7.0% ) 37 ( 2.3% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	0 ( 0.0% ) 67 ( 74.4% ) 16 ( 17.8% ) 7 ( 7.8% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	0 ( 0.0% ) 74 ( 87.1% ) 8 ( 9.4% ) 3 ( 3.5% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	2 ( 1.4% ) 106 ( 76.3% ) 16 ( 11.5% ) 13 ( 9.4% ) 2 ( 1.4% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	0 ( 0.0% ) 45 ( 76.3% ) 9 ( 15.3% ) 5 ( 8.5% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	0 ( 0.0% ) 91 ( 79.1% ) 12 ( 10.4% ) 11 ( 9.6% ) 1 ( 0.9% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	2 ( 0.2% ) 883 ( 81.4% ) 94 ( 8.7% ) 72 ( 6.6% ) 34 ( 3.1% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_6_stage_grp [factor]	1. 10 2. 30 3. 50 4. 70 5. 99	0 ( 0.0% ) 15 ( 93.8% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SS1977

• Description: This item is the derived “SEER Summary Stage 1977” from the CS algorithm (or EOD codes) effective with 2004 diagnosis.

• Rationale: The Collaborative Stage Data Collection System was designed by a joint task force including representatives from SEER, ACoS, CDC, NAACCR, NCRA, CCCR, CPAC, and AJCC, to provide a single uniform set of codes and rules for coding extent of disease (EOD) and stage information to meet the needs of all of the participating standard setters. When CS data items are coded, a computer algorithm provides the derivation of T, N, M, and stage-based on AJCC Cancer Staging Manual 6th & 7th Editions, SEER Summary Stage 1977, and SEER Summary Stage 2000. There are separate derived CS fields in the NAACCR record based on AJCC 6th Edition for 2004+ cases and AJCC 7th Edition for 2010+ cases.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3010

All data

st_css() #IMPORTANT!

  derivedss1977 <- as.factor(trimws(d[,"derivedss1977"]))
  new.d <- data.frame(new.d, derivedss1977)
  new.d <- apply_labels(new.d, derivedss1977 = "derived_ss1977")
temp.d <- data.frame (new.d.1, derivedss1977)
summarytools::view(dfSummary(new.d$derivedss1977, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedss1977 [labelled, factor]	derived_ss1977	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	1302 ( 81.9% ) 175 ( 11.0% ) 20 ( 1.3% ) 32 ( 2.0% ) 40 ( 2.5% ) 20 ( 1.3% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	67 ( 74.4% ) 16 ( 17.8% ) 1 ( 1.1% ) 4 ( 4.4% ) 2 ( 2.2% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	74 ( 87.1% ) 8 ( 9.4% ) 1 ( 1.2% ) 1 ( 1.2% ) 1 ( 1.2% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	109 ( 78.4% ) 16 ( 11.5% ) 3 ( 2.2% ) 7 ( 5.0% ) 3 ( 2.2% ) 1 ( 0.7% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	45 ( 76.3% ) 9 ( 15.3% ) 0 ( 0.0% ) 2 ( 3.4% ) 3 ( 5.1% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	92 ( 80.0% ) 15 ( 13.0% ) 2 ( 1.7% ) 3 ( 2.6% ) 3 ( 2.6% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	900 ( 82.9% ) 110 ( 10.1% ) 13 ( 1.2% ) 15 ( 1.4% ) 28 ( 2.6% ) 19 ( 1.8% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss1977 [factor]	1. 1 2. 2 3. 3 4. 4 5. 7 6. 9	15 ( 93.8% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SS2000

• Description: This item is the derived “SEER Summary Stage 2000” from the CS algorithm (or EOD codes) effective with 2004 diagnosis.

• Rationale: The Collaborative Stage Data Collection System was designed by a joint task force including representatives from SEER, ACoS, CDC, NAACCR, NCRA, CCCR, CPAC, and AJCC, to provide a single uniform set of codes and rules for coding extent of disease (EOD) and stage information to meet the needs of all of the participating standard setters. When CS data items are coded, a computer algorithm provides the derivation of T, N, M, and stage-based on AJCC Cancer Staging Manual 6th & 7th Editions, SEER Summary Stage 1977, and SEER Summary Stage 2000. There are separate derived CS fields in the NAACCR record based on AJCC 6th Edition for 2004+ cases and AJCC 7th Edition for 2010+ cases.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3020

All data

st_css() #IMPORTANT!

  derivedss2000 <- as.factor(d[,"derivedss2000"])
  levels(derivedss2000) <- list(In_situ.0="0",
                                          Localized.1="1",
                                          Direct_extension.2="2",
                                          Lymph_nodes_only.3="3",
                                          Extension_nodes.4="4",
                                          Distant.7="7",
                                          Unknown.9="9")
    derivedss2000 <- relevel(derivedss2000, ref="Localized.1")
    new.d <- data.frame(new.d, derivedss2000)
    new.d <- apply_labels(new.d, derivedss2000 = "Tumor Staging")
    #summary(new.d$derivedss2000)
temp.d <- data.frame (new.d.1, derivedss2000)
summarytools::view(dfSummary(new.d$derivedss2000, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedss2000 [labelled, factor]	Tumor Staging	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	1264 ( 79.5% ) 0 ( 0.0% ) 213 ( 13.4% ) 17 ( 1.1% ) 34 ( 2.1% ) 41 ( 2.6% ) 20 ( 1.3% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	61 ( 67.8% ) 0 ( 0.0% ) 22 ( 24.4% ) 1 ( 1.1% ) 4 ( 4.4% ) 2 ( 2.2% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	71 ( 83.5% ) 0 ( 0.0% ) 11 ( 12.9% ) 0 ( 0.0% ) 1 ( 1.2% ) 2 ( 2.4% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	103 ( 74.1% ) 0 ( 0.0% ) 22 ( 15.8% ) 3 ( 2.2% ) 7 ( 5.0% ) 3 ( 2.2% ) 1 ( 0.7% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	41 ( 69.5% ) 0 ( 0.0% ) 13 ( 22.0% ) 0 ( 0.0% ) 2 ( 3.4% ) 3 ( 5.1% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	85 ( 73.9% ) 0 ( 0.0% ) 22 ( 19.1% ) 1 ( 0.9% ) 4 ( 3.5% ) 3 ( 2.6% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	888 ( 81.8% ) 0 ( 0.0% ) 122 ( 11.2% ) 12 ( 1.1% ) 16 ( 1.5% ) 28 ( 2.6% ) 19 ( 1.8% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ss_2000 [factor]	1. Localized.1 2. In_situ.0 3. Direct_extension.2 4. Lymph_nodes_only.3 5. Extension_nodes.4 6. Distant.7 7. Unknown.9	15 ( 93.8% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 1

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

  • 00000 No secondary diagnoses documented

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3110

All data

st_css() #IMPORTANT!

  comorbidcomplication1 <- as.factor(d[,"comorbidcomplication1"])
  levels(comorbidcomplication1) <- list(No_secondary.0="0")
    new.d <- data.frame(new.d, comorbidcomplication1)
    new.d <- apply_labels(new.d, comorbidcomplication1 = "comorbid_complication1")
    #summary(new.d$comorbidcomplication1)
temp.d <- data.frame (new.d.1, comorbidcomplication1)
summarytools::view(dfSummary(new.d$comorbidcomplication1, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication1 [labelled, factor]	comorbid_complication1	1. No_secondary.0	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication1 [factor]	1. No_secondary.0	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 2

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3120

All data

st_css() #IMPORTANT!

  comorbidcomplication2 <- as.factor(d[,"comorbidcomplication2"])
    new.d <- data.frame(new.d, comorbidcomplication2)
    new.d <- apply_labels(new.d, comorbidcomplication2 = "comorbid_complication2")
    #summary(new.d$comorbidcomplication2)
temp.d <- data.frame (new.d.1, comorbidcomplication2)
summarytools::view(dfSummary(new.d$comorbidcomplication2, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication2 [labelled, factor]	comorbid_complication2	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	1 ( 1.1% ) 5 ( 5.6% ) 2 ( 2.2% ) 5 ( 5.6% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 4 ( 4.4% ) 1 ( 1.1% ) 2 ( 2.2% ) 1 ( 1.1% ) 1 ( 1.1% ) 21 ( 23.3% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 3 ( 3.3% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 5 ( 5.6% ) 1 ( 1.1% ) 1 ( 1.1% ) 2 ( 2.2% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 1 ( 1.1% ) 2 ( 2.2% ) 2 ( 2.2% )		2077 (95.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	0 ( 0.0% ) 1 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 29.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.9% ) 1 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.9% ) 0 ( 0.0% ) 1 ( 5.9% ) 2 ( 11.8% ) 1 ( 5.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		157 (90.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	1 ( 1.5% ) 4 ( 5.9% ) 2 ( 2.9% ) 5 ( 7.4% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 4 ( 5.9% ) 1 ( 1.5% ) 2 ( 2.9% ) 1 ( 1.5% ) 1 ( 1.5% ) 14 ( 20.6% ) 0 ( 0.0% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 2 ( 2.9% ) 0 ( 0.0% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 4 ( 5.9% ) 1 ( 1.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 1 ( 1.5% ) 2 ( 2.9% ) 2 ( 2.9% )		222 (76.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication2 [factor]	1. 13644 2. 25000 3. 27200 4. 27240 5. 27400 6. 27490 7. 27800 8. 27801 9. 28590 10. 30510 11. 35180 12. 36590 13. 40100 14. 40110 15. 40190 16. 40493 17. 42400 18. 44422 19. 47790 20. 53081 21. 55090 22. 56010 23. 56410 24. 56800 25. 57150 26. 57390 27. 5780  · 28. 57810 29. 5849  · 30. 59410 31. 5989  · 32. 59900 33. 60000 34. 60001 35. 60290 36. 60784 37. 64800 38. 69010 39. 71690 40. 7213  · 41. 72660 42. 72950 43. 72981 44. 78020 45. 78863 46. 78900 47. 79093 48. 99990	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 40.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		11 (68.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 3

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3130

All data

st_css() #IMPORTANT!

  comorbidcomplication3 <- as.factor(d[,"comorbidcomplication3"])
    new.d <- data.frame(new.d, comorbidcomplication3)
    new.d <- apply_labels(new.d, comorbidcomplication3 = "comorbid_complication3")
    #summary(new.d$comorbidcomplication3)
temp.d <- data.frame (new.d.1, comorbidcomplication3)
summarytools::view(dfSummary(new.d$comorbidcomplication3, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication3 [labelled, factor]	comorbid_complication3	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	1 ( 1.7% ) 3 ( 5.1% ) 1 ( 1.7% ) 3 ( 5.1% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 2 ( 3.4% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 3 ( 5.1% ) 2 ( 3.4% ) 1 ( 1.7% ) 2 ( 3.4% ) 2 ( 3.4% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 2 ( 3.4% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 1 ( 1.7% ) 2 ( 3.4% ) 2 ( 3.4% ) 1 ( 1.7% ) 2 ( 3.4% ) 1 ( 1.7% )		2108 (97.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	0 ( 0.0% ) 2 ( 15.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.7% ) 1 ( 7.7% ) 0 ( 0.0% )		161 (92.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 3 ( 7.1% ) 1 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 4.8% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 0 ( 0.0% ) 1 ( 2.4% ) 2 ( 4.8% ) 2 ( 4.8% ) 0 ( 0.0% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 0 ( 0.0% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 0 ( 0.0% ) 1 ( 2.4% ) 1 ( 2.4% ) 1 ( 2.4% ) 0 ( 0.0% ) 1 ( 2.4% ) 1 ( 2.4% ) 2 ( 4.8% ) 2 ( 4.8% ) 0 ( 0.0% ) 1 ( 2.4% ) 1 ( 2.4% )		248 (85.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication3 [factor]	1. 24490 2. 25000 3. 27200 4. 27240 5. 27490 6. 2752  · 7. 27651 8. 27800 9. 30002 10. 30500 11. 30510 12. 32723 13. 35400 14. 40190 15. 40390 16. 41040 17. 41200 18. 41400 19. 41490 20. 4186  · 21. 42832 22. 43600 23. 49600 24. 53081 25. 58550 26. 60000 27. 60784 28. 68220 29. 69806 30. 700  · 31. 7051  · 32. 7070  · 33. 71590 34. 71689 35. 71690 36. 71696 37. 72240 38. 72291 39. 72950 40. 74685 41. 78057 42. 78843 43. 79029 44. 79093 45. 99990	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		12 (75.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 4

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3140

All data

st_css() #IMPORTANT!

  comorbidcomplication4 <- as.factor(d[,"comorbidcomplication4"])
    new.d <- data.frame(new.d, comorbidcomplication4)
    new.d <- apply_labels(new.d, comorbidcomplication4 = "comorbid_complication4")
    #summary(new.d$comorbidcomplication4)
temp.d <- data.frame (new.d.1, comorbidcomplication4)
summarytools::view(dfSummary(new.d$comorbidcomplication4, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication4 [labelled, factor]	comorbid_complication4	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	1 ( 2.6% ) 1 ( 2.6% ) 2 ( 5.3% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 3 ( 7.9% ) 1 ( 2.6% ) 1 ( 2.6% ) 2 ( 5.3% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 2 ( 5.3% ) 1 ( 2.6% ) 2 ( 5.3% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% ) 1 ( 2.6% )		2129 (98.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 2 ( 22.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% ) 1 ( 11.1% ) 0 ( 0.0% )		165 (94.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	1 ( 4.0% ) 0 ( 0.0% ) 2 ( 8.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 1 ( 4.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 1 ( 4.0% ) 1 ( 4.0% ) 1 ( 4.0% ) 1 ( 4.0% ) 2 ( 8.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 4.0% ) 2 ( 8.0% ) 1 ( 4.0% ) 2 ( 8.0% ) 1 ( 4.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 4.0% ) 0 ( 0.0% ) 1 ( 4.0% )		265 (91.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication4 [factor]	1. 25000 2. 27240 3. 27490 4. 27610 5. 27800 6. 27802 7. 28249 8. 28860 9. 28981 10. 30510 11. 36501 12. 37862 13. 40190 14. 41491 15. 4280  · 16. 42890 17. 53030 18. 56210 19. 58490 20. 58881 21. 5920  · 22. 59200 23. 60000 24. 60001 25. 60784 26. 72450 27. 73100 28. 78060 29. 78062 30. 78841 31. 79093 32. 99990	0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		12 (75.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 5

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3150

All data

st_css() #IMPORTANT!

  comorbidcomplication5 <- as.factor(d[,"comorbidcomplication5"])
    new.d <- data.frame(new.d, comorbidcomplication5)
    new.d <- apply_labels(new.d, comorbidcomplication5 = "comorbid_complication5")
    #summary(new.d$comorbidcomplication5)
temp.d <- data.frame (new.d.1, comorbidcomplication5)
summarytools::view(dfSummary(new.d$comorbidcomplication5, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication5 [labelled, factor]	comorbid_complication5	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 4 ( 14.3% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% ) 1 ( 3.6% )		2139 (98.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		169 (97.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	1 ( 5.0% ) 0 ( 0.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 0 ( 0.0% ) 1 ( 5.0% ) 0 ( 0.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 3 ( 15.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 0 ( 0.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 0 ( 0.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 1 ( 5.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.0% ) 1 ( 5.0% )		270 (93.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication5 [factor]	1. 13500 2. 25000 3. 27240 4. 27803 5. 29600 6. 29630 7. 30510 8. 35400 9. 36800 10. 37515 11. 40190 12. 43820 13. 45340 14. 59100 15. 5932  · 16. 59971 17. 60784 18. 70000 19. 7032  · 20. 78060 21. 78590 22. 78701 23. 78820 24. 78862 25. 99990	0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% )		13 (81.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 6

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3160

All data

st_css() #IMPORTANT!

  comorbidcomplication6 <- as.factor(d[,"comorbidcomplication6"])
    new.d <- data.frame(new.d, comorbidcomplication6)
    new.d <- apply_labels(new.d, comorbidcomplication6 = "comorbid_complication6")
    #summary(new.d$comorbidcomplication6)
temp.d <- data.frame (new.d.1, comorbidcomplication6)
summarytools::view(dfSummary(new.d$comorbidcomplication6, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication6 [labelled, factor]	comorbid_complication6	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	2 ( 9.5% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 2 ( 9.5% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 2 ( 9.5% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% ) 1 ( 4.8% )		2146 (99.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		172 (98.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	2 ( 12.5% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 2 ( 12.5% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% )		274 (94.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication6 [factor]	1. 27240 2. 30401 3. 35180 4. 40190 5. 41400 6. 41519 7. 43812 8. 4720  · 9. 5739  · 10. 59390 11. 60010 12. 60784 13. 72420 14. 73390 15. 78659 16. 78865 17. 79029 18. 79093	0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		13 (81.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 7

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3161

All data

st_css() #IMPORTANT!

  comorbidcomplication7 <- as.factor(d[,"comorbidcomplication7"])
    new.d <- data.frame(new.d, comorbidcomplication7)
    new.d <- apply_labels(new.d, comorbidcomplication7 = "comorbid_complication7")
    #summary(new.d$comorbidcomplication7)
temp.d <- data.frame (new.d.1, comorbidcomplication7)
summarytools::view(dfSummary(new.d$comorbidcomplication7, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication7 [labelled, factor]	comorbid_complication7	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% ) 1 ( 5.9% )		2150 (99.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		172 (98.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 0 ( 0.0% ) 1 ( 8.3% ) 1 ( 8.3% ) 0 ( 0.0% ) 1 ( 8.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 8.3% ) 1 ( 8.3% ) 0 ( 0.0% )		278 (95.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication7 [factor]	1. 25000 2. 26890 3. 27220 4. 27240 5. 27490 6. 27800 7. 30275 8. 32723 9. 41200 10. 58590 11. 72420 12. 78052 13. 78194 14. 78841 15. 79093 16. 81600 17. 9989  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% )		13 (81.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 8

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3162

All data

st_css() #IMPORTANT!

  comorbidcomplication8 <- as.factor(d[,"comorbidcomplication8"])
    new.d <- data.frame(new.d, comorbidcomplication8)
    new.d <- apply_labels(new.d, comorbidcomplication8 = "comorbid_complication8")
    #summary(new.d$comorbidcomplication8)
temp.d <- data.frame (new.d.1, comorbidcomplication8)
summarytools::view(dfSummary(new.d$comorbidcomplication8, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication8 [labelled, factor]	comorbid_complication8	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% ) 2 ( 15.4% ) 1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% ) 1 ( 7.7% )		2154 (99.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% )		172 (98.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	1 ( 12.5% ) 1 ( 12.5% ) 0 ( 0.0% ) 1 ( 12.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 12.5% ) 1 ( 12.5% ) 1 ( 12.5% ) 1 ( 12.5% ) 0 ( 0.0% ) 1 ( 12.5% )		282 (97.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication8 [factor]	1. 25000 2. 26890 3. 28521 4. 33829 5. 41401 6. 53550 7. 56010 8. 56400 9. 71941 10. 75310 11. 78863 12. 79981	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 1 ( 33.3% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		13 (81.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 9

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications during the patient’s hospital stay for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3163

All data

st_css() #IMPORTANT!

  comorbidcomplication9 <- as.factor(d[,"comorbidcomplication9"])
    new.d <- data.frame(new.d, comorbidcomplication9)
    new.d <- apply_labels(new.d, comorbidcomplication9 = "comorbid_complication9")
    #summary(new.d$comorbidcomplication9)
temp.d <- data.frame (new.d.1, comorbidcomplication9)
summarytools::view(dfSummary(new.d$comorbidcomplication9, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication9 [labelled, factor]	comorbid_complication9	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% )		2160 (99.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 1 ( 25.0% ) 1 ( 25.0% )		286 (98.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication9 [factor]	1. 32723 2. 41401 3. 60000 4. 71695 5. 72910 6. 73300 7. 78052	1 ( 33.3% ) 1 ( 33.3% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		13 (81.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

COMORBID/COMPLICATION 10

• Description: Records the patient’s pre-existing medical conditions, factors influencing health status, and/or complications for the treatment of this cancer using ICD-9-CM codes. All are considered secondary diagnoses.

• Rationale: Pre-existing medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care.

• Codes (Refer to the most recent version of STORE for additional instructions.) ICD-9-CM Codes 00100-13980, 24000-99990, E8700-E8799, E9300-E9499, V0720-V0739, V1000-V1590, V2220- V2310, V2540, V4400-V4589, and V5041-V5049.

• Leave blank if no further secondary diagnosis.

• Note: For comorbid conditions (ICD-9-CM codes 00100-13980 and 24000-99990), there is an assumed decimal point between the third and fourth characters. For complications (ICD-9-CM codes E8700-E8799 and E9300-E9499), there is an assumed decimal point between the fourth and fifth characters. For conditions influencing health status and contact with health services (ICD-9-CM codes V0720-V0739, V1000-V1590, V2220-V2310, V2540, V4400-V4589, and V5041-V5049), there is an assumed decimal point between the third and fourth characters.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3164

All data

st_css() #IMPORTANT!

  comorbidcomplication10 <- as.factor(d[,"comorbidcomplication10"])
    new.d <- data.frame(new.d, comorbidcomplication10)
    new.d <- apply_labels(new.d, comorbidcomplication10 = "comorbid_complication10")
    #summary(new.d$comorbidcomplication10)
temp.d <- data.frame (new.d.1, comorbidcomplication10)
summarytools::view(dfSummary(new.d$comorbidcomplication10, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbidcomplication10 [labelled, factor]	comorbid_complication10	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 1 ( 20.0% )		2162 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	1 ( 25.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 1 ( 25.0% )		286 (98.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	comorbid_complication10 [factor]	1. 25720 2. 33381 3. 4019  · 4. 53560 5. 78841	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		15 (93.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

ICD REVISION COMORBID

• Description: This item indicates the coding system in which the Comorbidities and Complications (secondary diagnoses) codes are provided.

• Rationale: he CoC currently requires the collection and reporting of up to 10 ICD-9-CM codes describing secondary diagnoses for patients hospitalized for cancer treatment. Currently the use of ICD-10-CM is not mandatory in U.S. hospitals, though it may become so in the future. In the event this occurs cancer registries that maintain or collect this information will need to differentiate between ICD-9-CM and ICD-10-CM code use. The code values and definitions for this item would be expanded as necessary. Allowable codes reported in the Comorbidity and Complications items in STORE would be re-assessed at the same time.

• Codes

  • 0 No comorbidities or complications recorded in patient’s record
  • 1 ICD-10-CM
  • 9 ICD-9-CM
  • Blank Comorbidities and Complications not collected

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3165

All data

st_css() #IMPORTANT!

  icdrevisioncomorbid <- as.factor(d[,"icdrevisioncomorbid"])
  levels(icdrevisioncomorbid) <- list(No_in_record.0="0",
                                        ICD_10_CM.1 = "1", 
                                         ICD_9_CM.9 = "9"
                                        )
    new.d <- data.frame(new.d, icdrevisioncomorbid)
    new.d <- apply_labels(new.d, icdrevisioncomorbid = "icd_revision_comorbid")
    #summary(new.d$icdrevisioncomorbid)
temp.d <- data.frame (new.d.1, icdrevisioncomorbid)
summarytools::view(dfSummary(new.d$icdrevisioncomorbid, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icdrevisioncomorbid [labelled, factor]	icd_revision_comorbid	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	97 ( 35.9% ) 142 ( 52.6% ) 31 ( 11.5% )		1897 (87.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	86 ( 51.2% ) 55 ( 32.7% ) 27 ( 16.1% )		6 (3.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	0 ( 0.0% ) 87 ( 100.0% ) 0 ( 0.0% )		203 (70.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	icd_revision_comorbid [factor]	1. No_in_record.0 2. ICD_10_CM.1 3. ICD_9_CM.9	11 ( 73.3% ) 0 ( 0.0% ) 4 ( 26.7% )		1 (6.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE MST DEFN SRG

• Description: Date of most definitive surgical resection of the primary site performed as part of the first course of treatment. See Chapter X for date format. Use RX DATE MST DEFN SRG FLAG [3171] if there is no appropriate or known date for this item.

Formerly RX Date–Most Defin Surg.

• Rationale: This item is used to measure lag time between diagnosis and the most definitive surgery of the primary site or survival following the procedure. It also is used in conjunction with RX Date Surg Disch [3180] to calculate the duration of hospitalization following the most definitive primary site surgical procedure to evaluate treatment efficacy.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3170

All data

st_css() #IMPORTANT!

  rxdatemostdefinsurg <- as.factor(d[,"rxdatemostdefinsurg"])
 
    new.d <- data.frame(new.d, rxdatemostdefinsurg)
    new.d <- apply_labels(new.d, rxdatemostdefinsurg = "rx_date_most_defin_surg")
    #summary(new.d$rxdatemostdefinsurg)
temp.d <- data.frame (new.d.1, rxdatemostdefinsurg)
summarytools::view(dfSummary(new.d$rxdatemostdefinsurg, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatemostdefinsurg [labelled, factor]	rx_date_most_defin_surg	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 5 ( 0.5% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 3 ( 0.3% ) 7 ( 0.7% ) 2 ( 0.2% ) 1 ( 0.1% ) 2 ( 0.2% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 5 ( 0.5% ) 2 ( 0.2% ) 6 ( 0.6% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 2 ( 0.2% ) 2 ( 0.2% ) 11 ( 1.1% ) 2 ( 0.2% ) 3 ( 0.3% ) 1 ( 0.1% ) 1 ( 0.1% ) 1 ( 0.1% ) 911 ( 89.9% )		1154 (53.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 4.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 91 ( 86.7% )		84 (44.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 45 ( 93.8% )		126 (72.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 2.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 4.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 128 ( 88.9% )		93 (39.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 3.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 78 ( 91.8% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 2 ( 1.1% ) 1 ( 0.6% ) 0 ( 0.0% ) 3 ( 1.7% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 2 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 159 ( 87.8% )		109 (37.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 2 ( 0.5% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 3 ( 0.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 2 ( 0.5% ) 1 ( 0.2% ) 0 ( 0.0% ) 3 ( 0.7% ) 1 ( 0.2% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.5% ) 2 ( 0.5% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 410 ( 92.6% )		644 (59.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_most_defin_surg [factor]	1. 20120699 2. 20120999 3. 20130399 4. 20131199 5. 20140299 6. 20140599 7. 20141199 8. 201501  · 9. 201502  · 10. 20150212 11. 20150219 12. 20150223 13. 20150226 14. 201503  · 15. 20150310 16. 20150316 17. 20150317 18. 20150326 19. 20150399 20. 201504  · 21. 20150401 22. 20150402 23. 20150406 24. 20150407 25. 20150413 26. 20150414 27. 20150415 28. 20150416 29. 20150421 30. 20150423 31. 20150427 32. 20150428 33. 20150499 34. 201505  · 35. 20150501 36. 20150504 37. 20150506 38. 20150507 39. 20150511 40. 20150514 41. 20150521 42. 20150527 43. 20150528 44. 20150599 45. 201506  · 46. 20150603 47. 20150605 48. 20150610 49. 20150611 50. 20150612 [ 411 others ]	1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		9 (56.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RAD–BOOST RX MODALITY

• Description: Records the dominant modality of radiation therapy used to deliver the most clinically significant boost dose to the primary volume of interest during the first course of treatment. This is accomplished with external beam fields of reduced size (relative to the regional treatment fields), implants, stereotactic radiosurgery, conformal therapy, or intensity-modulated radiation therapy. External beam boosts may consist of two or more successive phases with progressively smaller fields, and they are generally coded as a single entity. This field is used with Rad–Regional RX Modality [1570].

• Rationale: Radiation treatment frequently is delivered in two or more phases that can be summarized as regional and boost treatments. A boost dose is administered to a volume within the regional volume. For outcomes analysis, the modalities used for each of these phases can be very important

• Codes

  • 00 No boost treatment
  • 20 External beam, NOS
  • 21 Orthovoltage
  • 22 Cobalt-60, Cesium-137
  • 23 Photons (2-5 MV)
  • 24 Photons (6-10 MV)
  • 25 Photons (11-19 MV)
  • 26 Photons (> 19 MV)
  • 27 Photons (mixed energies)
  • 28 Electrons
  • 29 Photons and electrons mixed
  • 30 Neutrons, with or without photons/electrons
  • 31 IMRT
  • 32 Conformal or 3-D therapy
  • 40 Protons
  • 41 Stereotactic radiosurgery, NOS
  • 42 Linac radiosurgery
  • 43 Gamma Knife
  • 50 Brachytherapy, NOS
  • 51 Brachytherapy, Intracavitary, LDR
  • 52 Brachytherapy, Intracavitary, HDR
  • 53 Brachytherapy, Interstitial, LDR
  • 54 Brachytherapy, Interstitial, HDR
  • 55 Radium
  • 60 Radio-isotopes, NOS
  • 61 Strontium - 89
  • 62 Strontium - 90
  • 98 Other, NOS
  • 99 Unknown

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3200

All data

st_css() #IMPORTANT!

  radboostrxmodality <- as.factor(d[,"radboostrxmodality"])
  levels(radboostrxmodality) <- list(No_boost_tx.0="0",
                                     External_beam_NOS.20="20",
                                     Photons_6_10_MV.24="24", 
                                     Photons_11_19_MV.25="25",
                                     Photons_mixed.27="27",
                                     Electrons.28 = "28",
                                     IMRT.31 = "31",
                                     Conformal_or_3D.32="32",
                                     Protons.40="40",
                                     Brachytherapy_NOS.50="50",
                                     Brachy_Intracavitary_LDR.51="51",
                                     Brachy_Intracavitary_HDR.52="52",
                                     Brachy_Interstitial_LDR.53="53",
                                     Brachy_Interstitial_HDR.54="54",
                                     Unknown.99 = "99"
                                        )
    new.d <- data.frame(new.d, radboostrxmodality)
    new.d <- apply_labels(new.d, radboostrxmodality = "rad_boost_rx_modality")
    #summary(new.d$radboostrxmodality)
temp.d <- data.frame (new.d.1, radboostrxmodality)
summarytools::view(dfSummary(new.d$radboostrxmodality, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	radboostrxmodality [labelled, factor]	rad_boost_rx_modality	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR. 12. Brachy_Intracavitary_HDR. 13. Brachy_Interstitial_LDR.5 14. Brachy_Interstitial_HDR.5 15. Unknown.99	0 ( 0.0% ) 14 ( 4.6% ) 23 ( 7.5% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 126 ( 41.0% ) 2 ( 0.7% ) 2 ( 0.7% ) 10 ( 3.3% ) 3 ( 1.0% ) 2 ( 0.7% ) 95 ( 30.9% ) 14 ( 4.6% ) 13 ( 4.2% )		1860 (85.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR.51 12. Brachy_Intracavitary_HDR.52 13. Brachy_Interstitial_LDR.53 14. Brachy_Interstitial_HDR.54 15. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR.51 12. Brachy_Intracavitary_HDR.52 13. Brachy_Interstitial_LDR.53 14. Brachy_Interstitial_HDR.54 15. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR.51 12. Brachy_Intracavitary_HDR.52 13. Brachy_Interstitial_LDR.53 14. Brachy_Interstitial_HDR.54 15. Unknown.99	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR.51 12. Brachy_Intracavitary_HDR.52 13. Brachy_Interstitial_LDR.53 14. Brachy_Interstitial_HDR.54 15. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR. 12. Brachy_Intracavitary_HDR. 13. Brachy_Interstitial_LDR.5 14. Brachy_Interstitial_HDR.5 15. Unknown.99	0 ( 0.0% ) 7 ( 11.5% ) 5 ( 8.2% ) 1 ( 1.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 33 ( 54.1% ) 0 ( 0.0% ) 2 ( 3.3% ) 3 ( 4.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 8 ( 13.1% )		229 (79.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR. 12. Brachy_Intracavitary_HDR. 13. Brachy_Interstitial_LDR.5 14. Brachy_Interstitial_HDR.5 15. Unknown.99	0 ( 0.0% ) 7 ( 2.8% ) 18 ( 7.3% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 93 ( 37.8% ) 2 ( 0.8% ) 0 ( 0.0% ) 7 ( 2.8% ) 3 ( 1.2% ) 2 ( 0.8% ) 94 ( 38.2% ) 13 ( 5.3% ) 5 ( 2.0% )		841 (77.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_boost_tx.0 2. External_beam_NOS.20 3. Photons_6_10_MV.24 4. Photons_11_19_MV.25 5. Photons_mixed.27 6. Electrons.28 7. IMRT.31 8. Conformal_or_3D.32 9. Protons.40 10. Brachytherapy_NOS.50 11. Brachy_Intracavitary_LDR.51 12. Brachy_Intracavitary_HDR.52 13. Brachy_Interstitial_LDR.53 14. Brachy_Interstitial_HDR.54 15. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RAD–BOOST DOSE CGY

• Description: Records the additional dose delivered to that part of the treatment volume encompassed by the boost fields or devices. The unit of measure is centiGray (cGy).

• Rationale: To evaluate patterns of radiation oncology care, it is necessary to describe the boost radiation dose. A boost dose is administered to a volume within the regional volume. As in chemotherapy, outcomes are strongly related to the dose delivered.

• Codes

  • (Fill blanks) Record the actual boost dose delivered
  • 00000 Boost radiation therapy was not administered
  • 88888 Not applicable, brachytherapy or radioisotopes administered to the patient
  • 99999 Boost radiation therapy administered, boost dose unknown

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3210

All data

st_css() #IMPORTANT!

  radboostdosecgy <- as.factor(d[,"radboostdosecgy"])
  
    new.d <- data.frame(new.d, radboostdosecgy)
    new.d <- apply_labels(new.d, radboostdosecgy = "rad_boost_dose_cgy")
    #summary(new.d$radboostdosecgy)
temp.d <- data.frame (new.d.1, radboostdosecgy)
summarytools::view(dfSummary(new.d$radboostdosecgy, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	radboostdosecgy [labelled, factor]	rad_boost_dose_cgy	No levels defined	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX DATE SYSTEMIC

• Description: Date of initiation of systemic therapy that is part of the first course of treatment. Systemic therapy includes the administration of chemotherapy agents, hormone agents, biological response modifiers, bone marrow transplants, stem cell harvests, and surgical and/or radiation endocrine therapy. See Chapter X for date format. Use RX DATE SYSTEMIC FLAG [3231] if there is no appropriate or known date for this item.

Formerly RX Date–Systemic.

• Rationale: Collecting dates for each treatment modality allows the sequencing of multiple treatments and aids in the evaluation of time intervals from diagnosis to treatment and from treatment to recurrence.

• date var

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3230

All data

st_css() #IMPORTANT!

  rxdatesystemic <- as.factor(d[,"rxdatesystemic"])
 
    new.d <- data.frame(new.d, rxdatesystemic)
    new.d <- apply_labels(new.d, rxdatesystemic = "rx_date_systemic")
    #summary(new.d$rxdatesystemic)
temp.d <- data.frame (new.d.1, rxdatesystemic)
summarytools::view(dfSummary(new.d$rxdatesystemic, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxdatesystemic [labelled, factor]	rx_date_systemic	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 5 ( 1.1% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 6 ( 1.3% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 2 ( 0.4% ) 1 ( 0.2% ) 1 ( 0.2% ) 1 ( 0.2% ) 406 ( 85.8% )		1694 (78.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 32 ( 86.5% )		152 (80.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 42 ( 91.3% )		128 (73.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 6.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 38 ( 84.4% )		192 (81.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.3% ) 39 ( 90.7% )		131 (75.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 1 ( 1.3% ) 0 ( 0.0% ) 1 ( 1.3% ) 1 ( 1.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 62 ( 80.5% )		213 (73.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.9% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 0.9% ) 1 ( 0.4% ) 2 ( 0.9% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 1 ( 0.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 1 ( 0.4% ) 0 ( 0.0% ) 193 ( 86.2% )		863 (79.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rx_date_systemic [factor]	1. 20130499 2. 2015  · 3. 201501  · 4. 20150116 5. 20150126 6. 201502  · 7. 20150210 8. 20150211 9. 20150217 10. 201503  · 11. 20150306 12. 20150326 13. 20150399 14. 201504  · 15. 20150401 16. 20150410 17. 20150415 18. 20150428 19. 20150499 20. 201505  · 21. 20150504 22. 20150505 23. 20150507 24. 20150509 25. 20150514 26. 20150515 27. 20150519 28. 20150521 29. 20150526 30. 20150528 31. 201506  · 32. 20150601 33. 20150602 34. 20150604 35. 20150608 36. 20150611 37. 20150612 38. 20150615 39. 20150616 40. 20150618 41. 20150619 42. 20150623 43. 20150625 44. 20150626 45. 20150627 46. 20150699 47. 20150702 48. 20150709 49. 20150727 50. 20150799 [ 237 others ]	1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		15 (93.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

RX SUMM–TRANSPLNT/ENDOCR

• Description: Identifies systemic therapeutic procedures administered as part of the first course of treatment at this and all other facilities. If none of these procedures were administered then this item records the reason they were not performed. These include bone marrow transplants, stem cell harvests, surgical and/or radiation endocrine therapy.

• Rationale: This data item allows the evaluation of patterns of treatment, which involve the alteration of the immune system or change the patient’s response to tumor cells but do not involve the administration of antineoplastic agents.

• Codes

  • 00 No transplant procedure or endocrine therapy was administered as part of first course therapy; diagnosed at autopsy
  • 10 Bone marrow transplant procedure was administered, but the type was not specified.
  • 11 Bone marrow transplant-autologous
  • 12 Bone marrow transplant-allogeneic
  • 20 Stem cell harvest and infusion
  • 30 Endocrine surgery and/or endocrine radiation therapy.
  • 40 Combination of endocrine surgery and/or radiation with a transplant procedure. (combination of codes 30 and 10, 11, 12 or 20).
  • 82 Hematologic transplant and/or endocrine surgery/radiation was not recommended/administered because it was contraindicated due to patient risk factors (i.e., comorbid conditions, advanced age).
  • 85 Hematologic transplant and/or endocrine surgery/radiation was not administered because the patient died prior to planned or recommended therapy.
  • 86 Hematologic transplant and/or endocrine surgery/radiation was not administered. It was recommended by the patient’s physician, but was not administered as part of first-course therapy. No reason was stated in the patient record.
  • 87 Hematologic transplant and/or endocrine surgery/radiation was not administered; it was recommended by the patient’s physician, but this treatment was refused by the patient, the patient’s family member, or the patient’s guardian; refusal noted in patient record
  • 88 Hematologic transplant and/or endocrine surgery/radiation was recommended, but it is unknown if it was administered
  • 99 It is unknown whether hematologic transplant and/or endocrine surgery/radiation was recommended or administered because it is not stated in patient record; death certificate-only cases

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3250

All data

st_css() #IMPORTANT!

  rxsummtransplntendocr <- as.factor(d[,"rxsummtransplntendocr"])
  levels(rxsummtransplntendocr) <- list(No_administered.0="0",
                                     Endo_surg_RT.30 = "30",
                                     Recomm_no_admin.86="86",
                                     Unknown.99 = "99"
                                        )
    new.d <- data.frame(new.d, rxsummtransplntendocr)
    new.d <- apply_labels(new.d, rxsummtransplntendocr = "rx_summ_transplnt_endocr")
    #summary(new.d$rxsummtransplntendocr)
temp.d <- data.frame (new.d.1, rxsummtransplntendocr)
summarytools::view(dfSummary(new.d$rxsummtransplntendocr, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rxsummtransplntendocr [labelled, factor]	rx_summ_transplnt_endocr	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	0 ( 0.0% ) 4 ( 25.0% ) 1 ( 6.2% ) 11 ( 68.8% )		2151 (99.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		236 (99.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 100.0% )		279 (96.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	0 ( 0.0% ) 3 ( 75.0% ) 1 ( 25.0% ) 0 ( 0.0% )		1083 (99.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	rad_boost_rx_modality [factor]	1. No_administered.0 2. Endo_surg_RT.30 3. Recomm_no_admin.86 4. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-7 T

• Description: This item is the derived AJCC “T” staging element from coded fields using the CS algorithm. Effective for cases diagnosed 2010+.

• Rationale: Derived AJCC-7 T can be used to evaluate disease spread at diagnosis, plan and track treatment patterns, and analyze outcomes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3400

All data

st_css() #IMPORTANT!

  derivedajcc7t <- as.factor(d[,"derivedajcc7t"])
  
    new.d <- data.frame(new.d, derivedajcc7t)
    new.d <- apply_labels(new.d, derivedajcc7t = "derived_ajcc_7t")
    #summary(new.d$derivedajcc7t)
temp.d <- data.frame (new.d.1, derivedajcc7t)
summarytools::view(dfSummary(new.d$derivedajcc7t, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc7t [labelled, factor]	derived_ajcc_7t	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	5 ( 0.3% ) 7 ( 0.4% ) 608 ( 38.3% ) 2 ( 0.1% ) 64 ( 4.0% ) 25 ( 1.6% ) 440 ( 27.7% ) 199 ( 12.5% ) 111 ( 7.0% ) 88 ( 5.5% ) 10 ( 0.6% ) 10 ( 0.6% ) 20 ( 1.3% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	0 ( 0.0% ) 0 ( 0.0% ) 20 ( 22.2% ) 0 ( 0.0% ) 5 ( 5.6% ) 5 ( 5.6% ) 38 ( 42.2% ) 1 ( 1.1% ) 13 ( 14.4% ) 7 ( 7.8% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	0 ( 0.0% ) 1 ( 1.2% ) 45 ( 52.9% ) 1 ( 1.2% ) 8 ( 9.4% ) 3 ( 3.5% ) 11 ( 12.9% ) 7 ( 8.2% ) 7 ( 8.2% ) 1 ( 1.2% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	2 ( 1.4% ) 1 ( 0.7% ) 48 ( 34.5% ) 0 ( 0.0% ) 7 ( 5.0% ) 2 ( 1.4% ) 47 ( 33.8% ) 8 ( 5.8% ) 12 ( 8.6% ) 10 ( 7.2% ) 1 ( 0.7% ) 0 ( 0.0% ) 1 ( 0.7% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	0 ( 0.0% ) 0 ( 0.0% ) 10 ( 16.9% ) 0 ( 0.0% ) 2 ( 3.4% ) 1 ( 1.7% ) 28 ( 47.5% ) 6 ( 10.2% ) 6 ( 10.2% ) 4 ( 6.8% ) 1 ( 1.7% ) 1 ( 1.7% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	1 ( 0.9% ) 1 ( 0.9% ) 27 ( 23.5% ) 0 ( 0.0% ) 7 ( 6.1% ) 2 ( 1.7% ) 46 ( 40.0% ) 12 ( 10.4% ) 11 ( 9.6% ) 7 ( 6.1% ) 0 ( 0.0% ) 1 ( 0.9% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	2 ( 0.2% ) 4 ( 0.4% ) 453 ( 41.8% ) 1 ( 0.1% ) 35 ( 3.2% ) 12 ( 1.1% ) 265 ( 24.4% ) 160 ( 14.7% ) 61 ( 5.6% ) 59 ( 5.4% ) 7 ( 0.6% ) 7 ( 0.6% ) 19 ( 1.8% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7t [factor]	1. 120 2. 150 3. 180 4. 199 5. 210 6. 220 7. 230 8. 299 9. 310 10. 320 11. 399 12. 400 13. 999	0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 31.2% ) 5 ( 31.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-7 N

• Description: This item is the derived AJCC “N” staging element from coded fields using the CS algorithm. Effective for cases diagnosed 2010+.

• Rationale: The CS Derived AJCC-7 N can be used to evaluate disease spread at diagnosis, plan and track treatment patterns, and analyze outcomes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3410

All data

st_css() #IMPORTANT!

  derivedajcc7n <- as.factor(d[,"derivedajcc7n"])
  
    new.d <- data.frame(new.d, derivedajcc7n)
    new.d <- apply_labels(new.d, derivedajcc7n = "derived_ajcc_7n")
    #summary(new.d$derivedajcc7n)
temp.d <- data.frame (new.d.1, derivedajcc7n)
summarytools::view(dfSummary(new.d$derivedajcc7n, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc7n [labelled, factor]	derived_ajcc_7n	1. 0  · 2. 100 3. 999	1496 ( 94.1% ) 65 ( 4.1% ) 28 ( 1.8% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	83 ( 92.2% ) 7 ( 7.8% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	83 ( 97.6% ) 2 ( 2.4% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	125 ( 89.9% ) 11 ( 7.9% ) 3 ( 2.2% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	57 ( 96.6% ) 2 ( 3.4% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	109 ( 94.8% ) 5 ( 4.3% ) 1 ( 0.9% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	1023 ( 94.3% ) 38 ( 3.5% ) 24 ( 2.2% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7n [factor]	1. 0  · 2. 100 3. 999	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-7 M

• Description: This item is the derived AJCC “M” staging element from coded fields using the CS algorithm. Effective for cases diagnosed 2010+.

• Rationale: Derived AJCC-7 M can be used to evaluate disease spread at diagnosis, plan and track treatment patterns, and analyze outcomes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3420

All data

st_css() #IMPORTANT!

  derivedajcc7m <- as.factor(d[,"derivedajcc7m"])
  
    new.d <- data.frame(new.d, derivedajcc7m)
    new.d <- apply_labels(new.d, derivedajcc7m = "derived_ajcc_7m")
    #summary(new.d$derivedajcc7m)
temp.d <- data.frame (new.d.1, derivedajcc7m)
summarytools::view(dfSummary(new.d$derivedajcc7m, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc7m [labelled, factor]	derived_ajcc_7m	1. 0  · 2. 110 3. 120 4. 130 5. 199	1550 ( 97.5% ) 7 ( 0.4% ) 30 ( 1.9% ) 1 ( 0.1% ) 1 ( 0.1% )		578 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	88 ( 97.8% ) 1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	83 ( 97.6% ) 1 ( 1.2% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	136 ( 97.8% ) 0 ( 0.0% ) 3 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	56 ( 94.9% ) 0 ( 0.0% ) 3 ( 5.1% ) 0 ( 0.0% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	113 ( 98.3% ) 0 ( 0.0% ) 2 ( 1.7% ) 0 ( 0.0% ) 0 ( 0.0% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	1058 ( 97.5% ) 5 ( 0.5% ) 20 ( 1.8% ) 1 ( 0.1% ) 1 ( 0.1% )		2 (0.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7m [factor]	1. 0  · 2. 110 3. 120 4. 130 5. 199	16 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED AJCC-7 STAGE GRP

• Description: This item is the derived AJCC “Stage Group” from coded fields using the CS algorithm. Effective for cases diagnosed 2010+.

• Rationale: The CS Derived AJCC-7 Stage Group can be used to evaluate disease spread at diagnosis, plan and track treatment patterns, and analyze outcomes.

• Codes (See the most current version of the Collaborative Stage Data Collection System (https://cancerstaging.org/cstage/Pages/default.aspx),13 for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3430

All data

st_css() #IMPORTANT!

  derivedajcc7stagegrp <- as.factor(d[,"derivedajcc7stagegrp"])
  
    new.d <- data.frame(new.d, derivedajcc7stagegrp)
    new.d <- apply_labels(new.d, derivedajcc7stagegrp = "derived_ajcc_7_stage_grp")
    #summary(new.d$derivedajcc7stagegrp)
temp.d <- data.frame (new.d.1, derivedajcc7stagegrp)
summarytools::view(dfSummary(new.d$derivedajcc7stagegrp, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedajcc7stagegrp [labelled, factor]	derived_ajcc_7_stage_grp	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	196 ( 12.3% ) 411 ( 25.9% ) 678 ( 42.7% ) 171 ( 10.8% ) 96 ( 6.0% ) 36 ( 2.3% )		579 (26.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	2 ( 2.2% ) 22 ( 24.4% ) 43 ( 47.8% ) 16 ( 17.8% ) 7 ( 7.8% ) 0 ( 0.0% )		99 (52.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	29 ( 34.1% ) 23 ( 27.1% ) 22 ( 25.9% ) 8 ( 9.4% ) 3 ( 3.5% ) 0 ( 0.0% )		89 (51.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	23 ( 16.5% ) 20 ( 14.4% ) 65 ( 46.8% ) 16 ( 11.5% ) 13 ( 9.4% ) 2 ( 1.4% )		98 (41.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	2 ( 3.4% ) 9 ( 15.3% ) 34 ( 57.6% ) 9 ( 15.3% ) 5 ( 8.5% ) 0 ( 0.0% )		115 (66.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	3 ( 2.6% ) 12 ( 10.4% ) 76 ( 66.1% ) 15 ( 13.0% ) 8 ( 7.0% ) 1 ( 0.9% )		175 (60.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	132 ( 12.2% ) 321 ( 29.6% ) 432 ( 39.9% ) 106 ( 9.8% ) 60 ( 5.5% ) 33 ( 3.0% )		3 (0.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_ajcc_7_stage_grp [factor]	1. 100 2. 320 3. 330 4. 500 5. 700 6. 999	5 ( 31.2% ) 4 ( 25.0% ) 6 ( 37.5% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% )		0 (0.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SEER PATH STG GRP

• Description: This data item is needed to store the results of the derived algorithmic calculation of Derived SEER Pathologic Stage Group.

• Rationale: The SEER Program is developing an algorithm to calculate clinical and pathologic stage group based on their T, N, and M components and additional information as needed to calculate stage. For example, for thyroid, additional information is needed on histology and age to calculate stage. Once the T, N, and M are known an algorithm can assign the stage group instead of a registrar having to look up the stage. There are also provisions for a separate field for directly assigned stage group if the registrar prefers entering it.

• Codes

  • 0 Stage 0
  • 0A Stage 0A
  • 0IS Stage 0is
  • 1 Stage I
  • 1A Stage IA
  • 1A1 Stage IA1
  • 1A2 Stage IA2
  • 1B Stage IB
  • 1B1 Stage IB1
  • 1B2 Stage IB2
  • 1C Stage IC
  • 1S Stage IS
  • 2 Stage II
  • 2A Stage IIA
  • 2A1 Stage IIA1
  • 2A2 Stage IIA2
  • 2B Stage IIB
  • 2C Stage IIC
  • 3 Stage III
  • 3A Stage IIIA
  • 3B Stage IIIB
  • 3C Stage IIIC
  • 3C1 Stage IIIC1
  • 3C2 Stage IIIC2
  • 4 Stage IV
  • 4A Stage IVA
  • 4A1 Stage IVA1
  • 4A2 Stage IVA2
  • 4B Stage IVB
  • 4C Stage IVC
  • OC Occult
  • 88 Not applicable
  • 99 Unknown
  • Blank Algorithm has not been run

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3605

All data

st_css() #IMPORTANT!

  derivedseerpathstggrp <- as.factor(d[,"derivedseerpathstggrp"])
  levels(derivedseerpathstggrp) <- list(Stage_I.1="1",
                        Stage_IIA.2A="2A",
                        Stage_IIB.2B="2B",
                        Stage_III.3="3",
                        Stage_IV.4="4",
                        Unknown.99="99")
    new.d <- data.frame(new.d, derivedseerpathstggrp)
    new.d <- apply_labels(new.d, derivedseerpathstggrp = "derived_seer_path_stg_grp")
    #summary(new.d$derivedseerpathstggrp)
temp.d <- data.frame (new.d.1, derivedseerpathstggrp)
summarytools::view(dfSummary(new.d$derivedseerpathstggrp, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedseerpathstggrp [labelled, factor]	derived_seer_path_stg_grp	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_path_stg_grp [factor]	1. Stage_I.1 2. Stage_IIA.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SEER PATH STG GRP

• Description: This data item is needed to store the results of the derived algorithmic calculation of Derived SEER Clinical Stage Group.

• Rationale: The SEER Program is developing an algorithm to calculate clinical and pathologic stage group based on their T, N, and M components and additional information as needed to calculate stage. For example, for thyroid, additional information is needed on histology and age to calculate stage. Once the T, N, and M are known an algorithm can assign the stage group instead of a registrar having to look up the stage. There are also provisions for a separate field for directly assigned stage group if the registrar prefers entering it.

• Codes

  • 0 Stage 0
  • 0A Stage 0A
  • 01S Stage 0is
  • 1 Stage I
  • 1A Stage IA
  • 1A1 Stage IA1
  • 1A2 Stage IA2
  • 1B Stage IB
  • 1B1 Stage IB1
  • 1C Stage IC
  • 1S Stage IS
  • 2 Stage 2
  • 2A Stage 2A
  • 2A1 Stage 2A1
  • 2A2 Stage 2A2
  • 2B Stage 2B
  • 2C Stage 2C
  • 3 Stage 3
  • 3A Stage 3A
  • 3B Stage 3B
  • 3C Stage 3C
  • 3C1 Stage 3C1
  • 3C2 Stage 3C2
  • 4 Stage 4
  • 4A Stage 4A
  • 4A1 Stage 4A1
  • 4A2 Stage 4A2
  • 4B Stage 4B
  • 4C Stage 4C
  • OC Stage OC
  • 88 Not applicable
  • 99 Unknown
  • Blank The algorithm has not been run

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3610

All data

st_css() #IMPORTANT!

  derivedseerclinstggrp <- as.factor(d[,"derivedseerclinstggrp"])
  levels(derivedseerclinstggrp) <- list(Stage_I.1="1",
                        Stage_2A.2A="2A",
                        Stage_2B.2B="2B",
                        Stage_3.3="3",
                        Stage_4.4="4",
                        Unknown.99="99")
    new.d <- data.frame(new.d, derivedseerclinstggrp)
    new.d <- apply_labels(new.d, derivedseerclinstggrp = "derived_seer_clin_stg_grp")
    #summary(new.d$derivedseerclinstggrp)
temp.d <- data.frame (new.d.1, derivedseerclinstggrp)
summarytools::view(dfSummary(new.d$derivedseerclinstggrp, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedseerclinstggrp [labelled, factor]	derived_seer_clin_stg_grp	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		2167 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_clin_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_2B.2B 4. Stage_3.3 5. Stage_4.4 6. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SEER CMB STG GRP

• Description: This data item is needed to store the results of the derived algorithmic calculation of SEER Combined Stage Group.

• Rationale: Rationale for change proposal (potential benefits of change): The SEER Program is developing an algorithm to calculate clinical and pathologic stage group based on their T, N, and M components and additional information as needed to calculate stage. For example, for thyroid, additional information is needed on histology and age to calculate stage. Once the T, N, and M are known an algorithm can assign the stage group instead of a registrar having to look up the stage. There are also provisions for a separate field for directly assigned stage group if the registrar prefers entering it.

• Codes

  • 0A Stage 0
  • 0IS Stage 0is
  • 1 Stage I
  • 1A Stage IA
  • 1A2 Stage IA2
  • 1B Stage IB
  • 1B1 Stage IB1
  • 1B2 Stage IB2
  • 1C Stage IC
  • 1S Stage IS
  • 2 Stage 2
  • 2A Stage 2A
  • 2A1 Stage
  • 2A2 Stage IIA2
  • 2B Stage IIB
  • 2C Stage IIC
  • 3 Stage III
  • 3A Stage IIIA
  • 3B Stage IIIB
  • 3C Stage IIIC
  • 3C1 Stage IIIC1
  • 3C2 Stage IIIC2
  • 4 Stage IV
  • 4A Stage IVA
  • 4A1 Stage IVA1
  • 4A2 Stage IV42
  • 4B Stage IVB
  • 4C Stage IV4C
  • OC Occult
  • 88 Not applicable
  • 99 Unknown
  • Blank The algorithm has not been run

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3614

All data

st_css() #IMPORTANT!

  derivedseercmbstggrp <- as.factor(trimws(d[,"derivedseercmbstggrp"]))
  # THIS CODING NEEDS TO BE CONFIRMED
  levels(derivedseercmbstggrp) <- list(Stage_I.1="1",
                                            Stage_2A.2A="2A",
                                          Stage_IIB.2B="2B",
                                          Stage_III.3="3",
                                          Stage_IV.4="4",
                                          Not_applicable.88="88",
                                          Unknown.99="99")
    new.d <- data.frame(new.d, derivedseercmbstggrp)
    new.d <- apply_labels(new.d, derivedseercmbstggrp = "Stage group based on their T, N, and M")
    #summary(new.d$derivedseercmbstggrp)
temp.d <- data.frame (new.d.1, derivedseercmbstggrp)
summarytools::view(dfSummary(new.d$derivedseercmbstggrp, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedseercmbstggrp [labelled, factor]	Stage group based on their T, N, and M	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	107 ( 21.2% ) 65 ( 12.9% ) 96 ( 19.0% ) 110 ( 21.8% ) 66 ( 13.1% ) 0 ( 0.0% ) 61 ( 12.1% )		1662 (76.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	14 ( 35.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 11 ( 28.2% ) 6 ( 15.4% ) 0 ( 0.0% ) 8 ( 20.5% )		150 (79.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	15 ( 16.9% ) 33 ( 37.1% ) 19 ( 21.3% ) 13 ( 14.6% ) 7 ( 7.9% ) 0 ( 0.0% ) 2 ( 2.2% )		85 (48.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	4 ( 4.1% ) 9 ( 9.2% ) 51 ( 52.0% ) 17 ( 17.3% ) 13 ( 13.3% ) 0 ( 0.0% ) 4 ( 4.1% )		139 (58.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	10 ( 12.0% ) 23 ( 27.7% ) 26 ( 31.3% ) 12 ( 14.5% ) 9 ( 10.8% ) 0 ( 0.0% ) 3 ( 3.6% )		91 (52.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	64 ( 32.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 57 ( 29.1% ) 31 ( 15.8% ) 0 ( 0.0% ) 44 ( 22.4% )		891 (82.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_cmb_stg_grp [factor]	1. Stage_I.1 2. Stage_2A.2A 3. Stage_IIB.2B 4. Stage_III.3 5. Stage_IV.4 6. Not_applicable.88 7. Unknown.99	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SEER COMBINED T

• Description: This new data item is needed to store the results of the derived algorithmic calculation of Derived SEER Combined T.

• Rationale: The SEER Program has collected data from 2004 on AJCC 6th T, N, M and stage and from 2010 on AJCC 7th T, N, M and stage based on algorithmic derivation from Collaborative Stage (CS) data. These data were based on combining information from both the clinical and pathologic into a combined (or ‘best’) derived T, N, M and stage group. SEER would like to continue to be able to derive a combined T, N, M and stage group in order to evaluate time trends in cancer incidence by stage. SEER is designing an algorithm to combine the clinical and pathologic information for T, N, and M into a derived combined T, N and M and then the combined T, N, and M and additional information as needed are used to derive a combined stage.

• Codes (See the most recent versions of the AJCC Cancer Staging Manual and STORE manual)

  • 88 Not applicable
  • Blank Not derived

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3616

All data

st_css() #IMPORTANT!

  derivedseercombinedt <- as.factor(d[,"derivedseercombinedt"])
  
    new.d <- data.frame(new.d, derivedseercombinedt)
    new.d <- apply_labels(new.d, derivedseercombinedt = "derived_seer_combined_t")
    #summary(new.d$derivedseercombinedt)
temp.d <- data.frame (new.d.1, derivedseercombinedt)
summarytools::view(dfSummary(new.d$derivedseercombinedt, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedseercombinedt [labelled, factor]	derived_seer_combined_t	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	9 ( 1.0% ) 2 ( 0.2% ) 403 ( 44.8% ) 17 ( 1.9% ) 26 ( 2.9% ) 16 ( 1.8% ) 34 ( 3.8% ) 1 ( 0.1% ) 9 ( 1.0% ) 8 ( 0.9% ) 1 ( 0.1% ) 9 ( 1.0% ) 16 ( 1.8% ) 15 ( 1.7% ) 4 ( 0.4% ) 211 ( 23.4% ) 1 ( 0.1% ) 69 ( 7.7% ) 48 ( 5.3% ) 1 ( 0.1% )		1267 (58.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	0 ( 0.0% ) 1 ( 1.0% ) 40 ( 41.7% ) 1 ( 1.0% ) 2 ( 2.1% ) 2 ( 2.1% ) 6 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 3.1% ) 0 ( 0.0% ) 3 ( 3.1% ) 1 ( 1.0% ) 2 ( 2.1% ) 0 ( 0.0% ) 24 ( 25.0% ) 0 ( 0.0% ) 6 ( 6.2% ) 5 ( 5.2% ) 0 ( 0.0% )		93 (49.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	0 ( 0.0% ) 0 ( 0.0% ) 44 ( 51.2% ) 0 ( 0.0% ) 9 ( 10.5% ) 1 ( 1.2% ) 6 ( 7.0% ) 0 ( 0.0% ) 1 ( 1.2% ) 0 ( 0.0% ) 1 ( 1.2% ) 1 ( 1.2% ) 0 ( 0.0% ) 3 ( 3.5% ) 0 ( 0.0% ) 7 ( 8.1% ) 0 ( 0.0% ) 10 ( 11.6% ) 3 ( 3.5% ) 0 ( 0.0% )		88 (50.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	0 ( 0.0% ) 0 ( 0.0% ) 17 ( 17.7% ) 4 ( 4.2% ) 3 ( 3.1% ) 1 ( 1.0% ) 6 ( 6.2% ) 0 ( 0.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 42 ( 43.8% ) 1 ( 1.0% ) 14 ( 14.6% ) 4 ( 4.2% ) 0 ( 0.0% )		141 (59.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	1 ( 1.2% ) 0 ( 0.0% ) 33 ( 39.8% ) 5 ( 6.0% ) 2 ( 2.4% ) 2 ( 2.4% ) 2 ( 2.4% ) 0 ( 0.0% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.4% ) 2 ( 2.4% ) 1 ( 1.2% ) 0 ( 0.0% ) 15 ( 18.1% ) 0 ( 0.0% ) 9 ( 10.8% ) 8 ( 9.6% ) 0 ( 0.0% )		91 (52.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	8 ( 1.5% ) 1 ( 0.2% ) 269 ( 49.9% ) 7 ( 1.3% ) 10 ( 1.9% ) 10 ( 1.9% ) 14 ( 2.6% ) 1 ( 0.2% ) 6 ( 1.1% ) 4 ( 0.7% ) 0 ( 0.0% ) 2 ( 0.4% ) 13 ( 2.4% ) 8 ( 1.5% ) 4 ( 0.7% ) 123 ( 22.8% ) 0 ( 0.0% ) 30 ( 5.6% ) 28 ( 5.2% ) 1 ( 0.2% )		548 (50.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_t [factor]	1. c1  · 2. c1A  · 3. c1C  · 4. c2  · 5. c2A  · 6. c2B  · 7. c2C  · 8. c3  · 9. c3A  · 10. c3B  · 11. c4  · 12. cX  · 13. p2  · 14. p2A  · 15. p2B  · 16. p2C  · 17. p3  · 18. p3A  · 19. p3B  · 20. p4  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SEER COMBINED N

• Description: This item is used to store the results of the source information selected for the derived algorithmic calculation of Combined T, N, and M.

• Rationale: The SEER Program has collected data from 2004 on AJCC 6th T, N, M and stage and from 2010 on AJCC 7th T, N, M and stage based on algorithmic derivation from Collaborative Stage (CS) data. These data were based on combining information from both the clinical and pathologic into a combined (or ‘best’) derived T, N, M and stage group. SEER would like to continue to be able to derive a combined T, N, M and stage group in order to evaluate time trends in cancer incidence by stage. SEER is designing an algorithm to combine the clinical and pathologic information for T, N, and M into a derived combined T, N and M and then the combined T, N, and M and additional information as needed are used to derive a combined stage. These derived combined T, N, M and stage items need to be new data items.

• Codes (See the most recent versions of the AJCC Cancer Staging Manual and STORE manual)

  • 88 Not applicable
  • Blank Not derived

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3618

All data

st_css() #IMPORTANT!

  derivedseercombinedn <- as.factor(d[,"derivedseercombinedn"])
  
    new.d <- data.frame(new.d, derivedseercombinedn)
    new.d <- apply_labels(new.d, derivedseercombinedn = "derived_seer_combined_n")
    #summary(new.d$derivedseercombinedn)
temp.d <- data.frame (new.d.1, derivedseercombinedn)
summarytools::view(dfSummary(new.d$derivedseercombinedn, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedseercombinedn [labelled, factor]	derived_seer_combined_n	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	608 ( 67.6% ) 22 ( 2.4% ) 22 ( 2.4% ) 219 ( 24.3% ) 27 ( 3.0% ) 2 ( 0.2% )		1267 (58.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	70 ( 72.9% ) 0 ( 0.0% ) 3 ( 3.1% ) 19 ( 19.8% ) 3 ( 3.1% ) 1 ( 1.0% )		93 (49.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	61 ( 70.9% ) 5 ( 5.8% ) 1 ( 1.2% ) 18 ( 20.9% ) 1 ( 1.2% ) 0 ( 0.0% )		88 (50.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	34 ( 35.4% ) 9 ( 9.4% ) 2 ( 2.1% ) 48 ( 50.0% ) 3 ( 3.1% ) 0 ( 0.0% )		141 (59.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	51 ( 61.4% ) 1 ( 1.2% ) 2 ( 2.4% ) 23 ( 27.7% ) 6 ( 7.2% ) 0 ( 0.0% )		91 (52.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	392 ( 72.7% ) 7 ( 1.3% ) 14 ( 2.6% ) 111 ( 20.6% ) 14 ( 2.6% ) 1 ( 0.2% )		548 (50.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_n [factor]	1. c0  · 2. c1  · 3. cX  · 4. p0  · 5. p1  · 6. pX  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

DERIVED SEER COMBINED M

• Description: This item is used to store the results of the source information selected for the derived algorithmic calculation of Combined T, N, and M.

• Rationale: The SEER Program has collected data from 2004 on AJCC 6th T, N, M and stage and from 2010 on AJCC 7th T, N, M and stage based on algorithmic derivation from Collaborative Stage (CS) data. These data were based on combining information from both the clinical and pathologic into a combined (or ‘best’) derived T, N, M and stage group. SEER would like to continue to be able to derive a combined T, N, M and stage group in order to evaluate time trends in cancer incidence by stage. SEER is designing an algorithm to combine the clinical and pathologic information for T, N, and M into a derived combined T, N and M and then the combined T, N, and M and additional information as needed are used to derive a combined stage. These derived combined T, N, M and stage items need to be new data items.

• Codes (See the most recent versions of the AJCC Cancer Staging Manual and STORE manual)

  • 88 Not applicable
  • Blank Not derived

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3620

All data

st_css() #IMPORTANT!

  derivedseercombinedm <- as.factor(d[,"derivedseercombinedm"])
  
    new.d <- data.frame(new.d, derivedseercombinedm)
    new.d <- apply_labels(new.d, derivedseercombinedm = "derived_seer_combined_m")
    #summary(new.d$derivedseercombinedm)
temp.d <- data.frame (new.d.1, derivedseercombinedm)
summarytools::view(dfSummary(new.d$derivedseercombinedm, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derivedseercombinedm [labelled, factor]	derived_seer_combined_m	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	867 ( 96.3% ) 4 ( 0.4% ) 3 ( 0.3% ) 20 ( 2.2% ) 3 ( 0.3% ) 2 ( 0.2% ) 1 ( 0.1% )		1267 (58.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	93 ( 96.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.1% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% )		93 (49.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	82 ( 95.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 3.5% ) 1 ( 1.2% ) 0 ( 0.0% ) 0 ( 0.0% )		88 (50.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	89 ( 92.7% ) 1 ( 1.0% ) 1 ( 1.0% ) 2 ( 2.1% ) 2 ( 2.1% ) 0 ( 0.0% ) 1 ( 1.0% )		141 (59.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	80 ( 96.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 3.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		91 (52.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	523 ( 97.0% ) 3 ( 0.6% ) 2 ( 0.4% ) 10 ( 1.9% ) 0 ( 0.0% ) 1 ( 0.2% ) 0 ( 0.0% )		548 (50.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	derived_seer_combined_m [factor]	1. c0  · 2. c1  · 3. c1A  · 4. c1B  · 5. c1C  · 6. p1A  · 7. p1C  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 1

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes (See the most recent versions of the AJCC Cancer Staging Manual and STORE manual)

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3780

All data

st_css() #IMPORTANT!

  secondarydiagnosis1 <- as.factor(d[,"secondarydiagnosis1"])
  
    new.d <- data.frame(new.d, secondarydiagnosis1)
    new.d <- apply_labels(new.d, secondarydiagnosis1 = "secondary_diagnosis_1")
    #summary(new.d$secondarydiagnosis1)
temp.d <- data.frame (new.d.1, secondarydiagnosis1)
summarytools::view(dfSummary(new.d$secondarydiagnosis1, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis1 [labelled, factor]	secondary_diagnosis_1	1. 0  ·	720 ( 100.0% )		1447 (66.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	52 ( 100.0% )		122 (70.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	75 ( 100.0% )		215 (74.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	589 ( 100.0% )		498 (45.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_1 [factor]	1. 0  ·	4 ( 100.0% )		12 (75.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 2

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3782

All data

st_css() #IMPORTANT!

  secondarydiagnosis2 <- as.factor(d[,"secondarydiagnosis2"])
  
    new.d <- data.frame(new.d, secondarydiagnosis2)
    new.d <- apply_labels(new.d, secondarydiagnosis2 = "secondary_diagnosis_2")
    #summary(new.d$secondarydiagnosis2)
temp.d <- data.frame (new.d.1, secondarydiagnosis2)
summarytools::view(dfSummary(new.d$secondarydiagnosis2, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis2 [labelled, factor]	secondary_diagnosis_2	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 [ 64 others ]	1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 20 ( 6.8% ) 1 ( 0.3% ) 4 ( 1.4% ) 7 ( 2.4% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 40 ( 13.6% ) 6 ( 2.0% ) 1 ( 0.3% ) 2 ( 0.7% ) 1 ( 0.3% ) 3 ( 1.0% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 38 ( 12.9% ) 1 ( 0.3% ) 4 ( 1.4% ) 1 ( 0.3% ) 2 ( 0.7% ) 2 ( 0.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 1 ( 0.3% ) 2 ( 0.7% ) 1 ( 0.3% ) 5 ( 1.7% ) 1 ( 0.3% ) 1 ( 0.3% ) 3 ( 1.0% ) 1 ( 0.3% ) 114 ( 38.8% )		1873 (86.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 51. J479  · 52. J841000 53. J954  · 54. J984  · 55. K219  · 56. K409000 57. K429  · 58. K429000 59. K611  · 60. K660  · 61. K7460  · 62. K768900 63. K802000 64. K862  · 65. K913  · 66. L732000 67. M069  · 68. M109  · 69. M129  · 70. M15  · 71. M160  · 72. M1990  · 73. M513600 74. N138  · 75. N139  · 76. N186  · 77. N189  · 78. N281  · 79. N289  · 80. N390  · 81. N393  · 82. N3941  · 83. N3943  · 84. N40  · 85. N40.0  · 86. N400  · 87. N40000  · 88. N401  · 89. N4010  · 90. N4110  · 91. N5201  · 92. N5203  · 93. N5231  · 94. N528  · 95. N529  · 96. R001  · 97. R030  · 98. R060000 99. R1030  · 100. R160000 101. R312  · 102. R319  · 103. R350  · 104. R351  · 105. R3510  · 106. R3915  · 107. R51  · 108. R5383  · 109. R590  · 110. R972  · 111. R9720  · 112. Z8042  · 113. Z86010  · 114. Z87891  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 51. J479  · 52. J841000 53. J954  · 54. J984  · 55. K219  · 56. K409000 57. K429  · 58. K429000 59. K611  · 60. K660  · 61. K7460  · 62. K768900 63. K802000 64. K862  · 65. K913  · 66. L732000 67. M069  · 68. M109  · 69. M129  · 70. M15  · 71. M160  · 72. M1990  · 73. M513600 74. N138  · 75. N139  · 76. N186  · 77. N189  · 78. N281  · 79. N289  · 80. N390  · 81. N393  · 82. N3941  · 83. N3943  · 84. N40  · 85. N40.0  · 86. N400  · 87. N40000  · 88. N401  · 89. N4010  · 90. N4110  · 91. N5201  · 92. N5203  · 93. N5231  · 94. N528  · 95. N529  · 96. R001  · 97. R030  · 98. R060000 99. R1030  · 100. R160000 101. R312  · 102. R319  · 103. R350  · 104. R351  · 105. R3510  · 106. R3915  · 107. R51  · 108. R5383  · 109. R590  · 110. R972  · 111. R9720  · 112. Z8042  · 113. Z86010  · 114. Z87891  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 51. J479  · 52. J841000 53. J954  · 54. J984  · 55. K219  · 56. K409000 57. K429  · 58. K429000 59. K611  · 60. K660  · 61. K7460  · 62. K768900 63. K802000 64. K862  · 65. K913  · 66. L732000 67. M069  · 68. M109  · 69. M129  · 70. M15  · 71. M160  · 72. M1990  · 73. M513600 74. N138  · 75. N139  · 76. N186  · 77. N189  · 78. N281  · 79. N289  · 80. N390  · 81. N393  · 82. N3941  · 83. N3943  · 84. N40  · 85. N40.0  · 86. N400  · 87. N40000  · 88. N401  · 89. N4010  · 90. N4110  · 91. N5201  · 92. N5203  · 93. N5231  · 94. N528  · 95. N529  · 96. R001  · 97. R030  · 98. R060000 99. R1030  · 100. R160000 101. R312  · 102. R319  · 103. R350  · 104. R351  · 105. R3510  · 106. R3915  · 107. R51  · 108. R5383  · 109. R590  · 110. R972  · 111. R9720  · 112. Z8042  · 113. Z86010  · 114. Z87891  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 [ 64 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 5 ( 10.9% ) 0 ( 0.0% ) 1 ( 2.2% ) 2 ( 4.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 8.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 4.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 6.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 4.3% ) 0 ( 0.0% ) 19 ( 41.3% )		128 (73.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 [ 64 others ]	1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.1% ) 6 ( 6.4% ) 1 ( 1.1% ) 2 ( 2.1% ) 2 ( 2.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.1% ) 16 ( 17.0% ) 3 ( 3.2% ) 1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 16 ( 17.0% ) 1 ( 1.1% ) 3 ( 3.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.1% ) 1 ( 1.1% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 29 ( 30.9% )		196 (67.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 [ 64 others ]	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 9 ( 5.8% ) 0 ( 0.0% ) 1 ( 0.6% ) 3 ( 1.9% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 20 ( 13.0% ) 3 ( 1.9% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 2 ( 1.3% ) 19 ( 12.3% ) 0 ( 0.0% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 1 ( 0.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 1.3% ) 1 ( 0.6% ) 4 ( 2.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 1 ( 0.6% ) 66 ( 42.9% )		933 (85.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_2 [factor]	1. A419  · 2. B182000 3. B20  · 4. E039  · 5. E081000 6. E1122  · 7. E1165  · 8. E116500 9. E1169  · 10. E118  · 11. E119  · 12. E119000 13. E669  · 14. E780  · 15. E7800  · 16. E782  · 17. E782000 18. E785  · 19. E785000 20. E835200 21. E876  · 22. G40909  · 23. G4733  · 24. G560  · 25. H40  · 26. H409  · 27. I10  · 28. I1000  · 29. I100000 30. I119  · 31. I120  · 32. I129  · 33. I251  · 34. I2510  · 35. I251000 36. I252  · 37. I341  · 38. I5022  · 39. I5042  · 40. I509  · 41. I700  · 42. I739  · 43. I82509  · 44. I878  · 45. J302  · 46. J449  · 47. J45  · 48. J4590  · 49. J45909  · 50. J459090 51. J479  · 52. J841000 53. J954  · 54. J984  · 55. K219  · 56. K409000 57. K429  · 58. K429000 59. K611  · 60. K660  · 61. K7460  · 62. K768900 63. K802000 64. K862  · 65. K913  · 66. L732000 67. M069  · 68. M109  · 69. M129  · 70. M15  · 71. M160  · 72. M1990  · 73. M513600 74. N138  · 75. N139  · 76. N186  · 77. N189  · 78. N281  · 79. N289  · 80. N390  · 81. N393  · 82. N3941  · 83. N3943  · 84. N40  · 85. N40.0  · 86. N400  · 87. N40000  · 88. N401  · 89. N4010  · 90. N4110  · 91. N5201  · 92. N5203  · 93. N5231  · 94. N528  · 95. N529  · 96. R001  · 97. R030  · 98. R060000 99. R1030  · 100. R160000 101. R312  · 102. R319  · 103. R350  · 104. R351  · 105. R3510  · 106. R3915  · 107. R51  · 108. R5383  · 109. R590  · 110. R972  · 111. R9720  · 112. Z8042  · 113. Z86010  · 114. Z87891  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 3

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3784

All data

st_css() #IMPORTANT!

  secondarydiagnosis3 <- as.factor(d[,"secondarydiagnosis3"])
  
    new.d <- data.frame(new.d, secondarydiagnosis3)
    new.d <- apply_labels(new.d, secondarydiagnosis3 = "secondary_diagnosis_3")
    #summary(new.d$secondarydiagnosis3)
temp.d <- data.frame (new.d.1, secondarydiagnosis3)
summarytools::view(dfSummary(new.d$secondarydiagnosis3, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis3 [labelled, factor]	secondary_diagnosis_3	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 [ 47 others ]	1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 11 ( 5.9% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 5 ( 2.7% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 17 ( 9.1% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 4 ( 2.1% ) 19 ( 10.2% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 3 ( 1.6% ) 1 ( 0.5% ) 1 ( 0.5% ) 2 ( 1.1% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 9 ( 4.8% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 1 ( 0.5% ) 73 ( 39.0% )		1980 (91.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 51. K5900  · 52. K603  · 53. L409  · 54. M10  · 55. M109  · 56. M1990  · 57. M199000 58. M47815  · 59. M478160 60. M549  · 61. N179  · 62. N183  · 63. N189  · 64. N281  · 65. N318  · 66. N3941  · 67. N40  · 68. N400  · 69. N401  · 70. N4289  · 71. N432  · 72. N5201  · 73. N529  · 74. N9971  · 75. N99842  · 76. R05  · 77. R200  · 78. R3100  · 79. R338  · 80. R339  · 81. R351  · 82. R3915  · 83. R5383  · 84. R590  · 85. R631  · 86. R9431  · 87. R972  · 88. R9720  · 89. Z6831  · 90. Z801  · 91. Z8546  · 92. Z8673  · 93. Z87891  · 94. Z880  · 95. Z955000 96. Z98890  · 97. Z992  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 51. K5900  · 52. K603  · 53. L409  · 54. M10  · 55. M109  · 56. M1990  · 57. M199000 58. M47815  · 59. M478160 60. M549  · 61. N179  · 62. N183  · 63. N189  · 64. N281  · 65. N318  · 66. N3941  · 67. N40  · 68. N400  · 69. N401  · 70. N4289  · 71. N432  · 72. N5201  · 73. N529  · 74. N9971  · 75. N99842  · 76. R05  · 77. R200  · 78. R3100  · 79. R338  · 80. R339  · 81. R351  · 82. R3915  · 83. R5383  · 84. R590  · 85. R631  · 86. R9431  · 87. R972  · 88. R9720  · 89. Z6831  · 90. Z801  · 91. Z8546  · 92. Z8673  · 93. Z87891  · 94. Z880  · 95. Z955000 96. Z98890  · 97. Z992  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 51. K5900  · 52. K603  · 53. L409  · 54. M10  · 55. M109  · 56. M1990  · 57. M199000 58. M47815  · 59. M478160 60. M549  · 61. N179  · 62. N183  · 63. N189  · 64. N281  · 65. N318  · 66. N3941  · 67. N40  · 68. N400  · 69. N401  · 70. N4289  · 71. N432  · 72. N5201  · 73. N529  · 74. N9971  · 75. N99842  · 76. R05  · 77. R200  · 78. R3100  · 79. R338  · 80. R339  · 81. R351  · 82. R3915  · 83. R5383  · 84. R590  · 85. R631  · 86. R9431  · 87. R972  · 88. R9720  · 89. Z6831  · 90. Z801  · 91. Z8546  · 92. Z8673  · 93. Z87891  · 94. Z880  · 95. Z955000 96. Z98890  · 97. Z992  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 [ 47 others ]	1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 5 ( 13.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 2 ( 5.4% ) 5 ( 13.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 14 ( 37.8% )		137 (78.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 [ 47 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.9% ) 1 ( 1.9% ) 5 ( 9.4% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 1 ( 1.9% ) 1 ( 1.9% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 11.3% ) 2 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 3.8% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 7.5% ) 0 ( 0.0% ) 1 ( 1.9% ) 0 ( 0.0% ) 0 ( 0.0% ) 19 ( 35.8% )		237 (81.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 [ 47 others ]	0 ( 0.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 6 ( 6.2% ) 1 ( 1.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 3.1% ) 0 ( 0.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 6 ( 6.2% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 2.1% ) 12 ( 12.4% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 5 ( 5.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.0% ) 1 ( 1.0% ) 40 ( 41.2% )		990 (91.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_3 [factor]	1. B1710  · 2. B182  · 3. E039  · 4. E039000 5. E1169  · 6. E119  · 7. E119000 8. E291  · 9. E6601  · 10. E663  · 11. E669  · 12. E669000 13. E78  · 14. E780  · 15. E7800  · 16. E782  · 17. E784  · 18. E785  · 19. E785000 20. E875  · 21. E876  · 22. G4730  · 23. G4733  · 24. G609000 25. G8929  · 26. H409  · 27. I10  · 28. I100000 29. I1129  · 30. I129  · 31. I2510  · 32. I495  · 33. I50  · 34. I509  · 35. I700000 36. I709000 37. I739  · 38. I7789  · 39. I82401  · 40. I898  · 41. I959  · 42. J302  · 43. J449  · 44. J45  · 45. J984  · 46. K219  · 47. K4020  · 48. K4090  · 49. K429000 50. K579000 51. K5900  · 52. K603  · 53. L409  · 54. M10  · 55. M109  · 56. M1990  · 57. M199000 58. M47815  · 59. M478160 60. M549  · 61. N179  · 62. N183  · 63. N189  · 64. N281  · 65. N318  · 66. N3941  · 67. N40  · 68. N400  · 69. N401  · 70. N4289  · 71. N432  · 72. N5201  · 73. N529  · 74. N9971  · 75. N99842  · 76. R05  · 77. R200  · 78. R3100  · 79. R338  · 80. R339  · 81. R351  · 82. R3915  · 83. R5383  · 84. R590  · 85. R631  · 86. R9431  · 87. R972  · 88. R9720  · 89. Z6831  · 90. Z801  · 91. Z8546  · 92. Z8673  · 93. Z87891  · 94. Z880  · 95. Z955000 96. Z98890  · 97. Z992  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 4

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3786

All data

st_css() #IMPORTANT!

  secondarydiagnosis4 <- as.factor(d[,"secondarydiagnosis4"])
  
    new.d <- data.frame(new.d, secondarydiagnosis4)
    new.d <- apply_labels(new.d, secondarydiagnosis4 = "secondary_diagnosis_4")
    #summary(new.d$secondarydiagnosis4)
temp.d <- data.frame (new.d.1, secondarydiagnosis4)
summarytools::view(dfSummary(new.d$secondarydiagnosis4, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis4 [labelled, factor]	secondary_diagnosis_4	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · [ 22 others ]	1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 6 ( 5.2% ) 1 ( 0.9% ) 1 ( 0.9% ) 2 ( 1.7% ) 1 ( 0.9% ) 3 ( 2.6% ) 9 ( 7.8% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 2 ( 1.7% ) 2 ( 1.7% ) 1 ( 0.9% ) 10 ( 8.7% ) 1 ( 0.9% ) 2 ( 1.7% ) 1 ( 0.9% ) 2 ( 1.7% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 2 ( 1.7% ) 5 ( 4.3% ) 1 ( 0.9% ) 1 ( 0.9% ) 2 ( 1.7% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 3 ( 2.6% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 1 ( 0.9% ) 2 ( 1.7% ) 27 ( 23.5% )		2052 (94.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · 51. N521  · 52. N528  · 53. R0781  · 54. R140  · 55. R312  · 56. R350  · 57. R351  · 58. R52  · 59. R634  · 60. R6882  · 61. R911  · 62. R972  · 63. R9720  · 64. Z6822  · 65. Z803  · 66. Z853  · 67. Z86010  · 68. Z87891  · 69. Z878910 70. Z91013  · 71. Z95810  · 72. Z992  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · 51. N521  · 52. N528  · 53. R0781  · 54. R140  · 55. R312  · 56. R350  · 57. R351  · 58. R52  · 59. R634  · 60. R6882  · 61. R911  · 62. R972  · 63. R9720  · 64. Z6822  · 65. Z803  · 66. Z853  · 67. Z86010  · 68. Z87891  · 69. Z878910 70. Z91013  · 71. Z95810  · 72. Z992  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · 51. N521  · 52. N528  · 53. R0781  · 54. R140  · 55. R312  · 56. R350  · 57. R351  · 58. R52  · 59. R634  · 60. R6882  · 61. R911  · 62. R972  · 63. R9720  · 64. Z6822  · 65. Z803  · 66. Z853  · 67. Z86010  · 68. Z87891  · 69. Z878910 70. Z91013  · 71. Z95810  · 72. Z992  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · [ 22 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 1 ( 3.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 1 ( 3.6% ) 5 ( 17.9% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 2 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.6% ) 0 ( 0.0% ) 8 ( 28.6% )		146 (83.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · [ 22 others ]	1 ( 3.8% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 1 ( 3.8% ) 1 ( 3.8% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 1 ( 3.8% ) 1 ( 3.8% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 7.7% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.8% ) 0 ( 0.0% ) 2 ( 7.7% ) 5 ( 19.2% )		264 (91.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · [ 22 others ]	0 ( 0.0% ) 1 ( 1.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 0 ( 0.0% ) 5 ( 8.2% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 2 ( 3.3% ) 6 ( 9.8% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 4 ( 6.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 0 ( 0.0% ) 4 ( 6.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 1 ( 1.6% ) 1 ( 1.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 14 ( 23.0% )		1026 (94.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_4 [factor]	1. B181  · 2. E039  · 3. E11321  · 4. E1139  · 5. E1169  · 6. E119  · 7. E119000 8. E559  · 9. E669  · 10. E780  · 11. E782  · 12. E785  · 13. E7850  · 14. E871  · 15. G4700  · 16. G4730  · 17. G4733  · 18. G8929  · 19. I10  · 20. I100000 21. I129  · 22. I251  · 23. I2510  · 24. I639000 25. I723000 26. J3089  · 27. J3489  · 28. J45909  · 29. J984  · 30. K219  · 31. K219000 32. K44900  · 33. K660  · 34. L2084  · 35. M109  · 36. M129  · 37. M170  · 38. M1712  · 39. M1990  · 40. M1A  · 41. M25512  · 42. M25669  · 43. M478180 44. M5410  · 45. M545000 46. N183  · 47. N289  · 48. N3289  · 49. N40  · 50. N401  · 51. N521  · 52. N528  · 53. R0781  · 54. R140  · 55. R312  · 56. R350  · 57. R351  · 58. R52  · 59. R634  · 60. R6882  · 61. R911  · 62. R972  · 63. R9720  · 64. Z6822  · 65. Z803  · 66. Z853  · 67. Z86010  · 68. Z87891  · 69. Z878910 70. Z91013  · 71. Z95810  · 72. Z992  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 5

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3788

All data

st_css() #IMPORTANT!

  secondarydiagnosis5 <- as.factor(d[,"secondarydiagnosis5"])
  
    new.d <- data.frame(new.d, secondarydiagnosis5)
    new.d <- apply_labels(new.d, secondarydiagnosis5 = "secondary_diagnosis_5")
    #summary(new.d$secondarydiagnosis5)
temp.d <- data.frame (new.d.1, secondarydiagnosis5)
summarytools::view(dfSummary(new.d$secondarydiagnosis5, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis5 [labelled, factor]	secondary_diagnosis_5	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · [ 2 others ]	1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 2 ( 2.9% ) 2 ( 2.9% ) 3 ( 4.3% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 3 ( 4.3% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 3 ( 4.3% ) 4 ( 5.7% ) 1 ( 1.4% ) 3 ( 4.3% ) 1 ( 1.4% ) 2 ( 2.9% ) 1 ( 1.4% ) 1 ( 1.4% ) 2 ( 2.9% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 3 ( 4.3% ) 2 ( 2.9% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 1 ( 1.4% ) 2 ( 2.9% )		2097 (96.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · 51. Z951  · 52. Z96643  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · 51. Z951  · 52. Z96643  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · 51. Z951  · 52. Z96643  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · [ 2 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 1 ( 5.3% ) 0 ( 0.0% ) 1 ( 5.3% ) 1 ( 5.3% ) 1 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 0 ( 0.0% ) 1 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 1 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 1 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 0 ( 0.0% ) 1 ( 5.3% ) 0 ( 0.0% ) 2 ( 10.5% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 5.3% ) 1 ( 5.3% ) 1 ( 5.3% ) 0 ( 0.0% ) 0 ( 0.0% )		155 (89.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · [ 2 others ]	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.1% ) 0 ( 0.0% ) 1 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.1% ) 1 ( 7.1% ) 0 ( 0.0% ) 1 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.1% ) 1 ( 7.1% ) 0 ( 0.0% ) 1 ( 7.1% ) 1 ( 7.1% ) 1 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 7.1% ) 1 ( 7.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		276 (95.2%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · [ 2 others ]	1 ( 2.7% ) 1 ( 2.7% ) 1 ( 2.7% ) 1 ( 2.7% ) 1 ( 2.7% ) 3 ( 8.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 3 ( 8.1% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 1 ( 2.7% ) 2 ( 5.4% ) 4 ( 10.8% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 5.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 1 ( 2.7% ) 1 ( 2.7% ) 1 ( 2.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 2.7% ) 2 ( 5.4% )		1050 (96.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_5 [factor]	1. B009  · 2. E039  · 3. E042  · 4. E119  · 5. E669  · 6. E785  · 7. G4730  · 8. G629  · 9. H3552  · 10. I071  · 11. I10  · 12. I2510  · 13. I252  · 14. I420  · 15. I739  · 16. J309  · 17. J449  · 18. K219  · 19. K219000 20. M109  · 21. M19011  · 22. M1990  · 23. M25122  · 24. M25561  · 25. M478150 26. M480200 27. M542  · 28. M549  · 29. M7581  · 30. N138  · 31. N182  · 32. N183  · 33. N189  · 34. N40  · 35. N400  · 36. N401  · 37. N411  · 38. R0602  · 39. R300  · 40. R350  · 41. R351  · 42. R739  · 43. R740  · 44. R809  · 45. R972  · 46. Z8042  · 47. Z87891  · 48. Z9079  · 49. Z9221  · 50. Z940  · 51. Z951  · 52. Z96643  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 6

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3790

All data

st_css() #IMPORTANT!

  secondarydiagnosis6 <- as.factor(d[,"secondarydiagnosis6"])
  
    new.d <- data.frame(new.d, secondarydiagnosis6)
    new.d <- apply_labels(new.d, secondarydiagnosis6 = "secondary_diagnosis_6")
    #summary(new.d$secondarydiagnosis6)
temp.d <- data.frame (new.d.1, secondarydiagnosis6)
summarytools::view(dfSummary(new.d$secondarydiagnosis6, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis6 [labelled, factor]	secondary_diagnosis_6	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 2 ( 4.2% ) 1 ( 2.1% ) 2 ( 4.2% ) 3 ( 6.2% ) 1 ( 2.1% ) 1 ( 2.1% ) 2 ( 4.2% ) 5 ( 10.4% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 2 ( 4.2% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 1 ( 2.1% ) 3 ( 6.2% ) 1 ( 2.1% ) 1 ( 2.1% ) 2 ( 4.2% ) 1 ( 2.1% ) 2 ( 4.2% ) 1 ( 2.1% )		2119 (97.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 2 ( 18.2% ) 1 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 9.1% ) 1 ( 9.1% )		163 (93.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	1 ( 10.0% ) 0 ( 0.0% ) 1 ( 10.0% ) 1 ( 10.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 10.0% ) 0 ( 0.0% ) 1 ( 10.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 10.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 10.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 10.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		280 (96.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	0 ( 0.0% ) 1 ( 3.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.7% ) 1 ( 3.7% ) 2 ( 7.4% ) 3 ( 11.1% ) 0 ( 0.0% ) 1 ( 3.7% ) 2 ( 7.4% ) 3 ( 11.1% ) 1 ( 3.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.7% ) 1 ( 3.7% ) 1 ( 3.7% ) 1 ( 3.7% ) 1 ( 3.7% ) 1 ( 3.7% ) 0 ( 0.0% ) 1 ( 3.7% ) 0 ( 0.0% ) 1 ( 3.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.7% ) 0 ( 0.0% ) 1 ( 3.7% ) 0 ( 0.0% ) 1 ( 3.7% ) 1 ( 3.7% ) 0 ( 0.0% )		1060 (97.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_6 [factor]	1. E041  · 2. E1122  · 3. E119  · 4. E119000 5. E669  · 6. E780  · 7. E7800  · 8. E785  · 9. E875  · 10. F328  · 11. G4730  · 12. I10  · 13. I251  · 14. I429  · 15. I7090  · 16. J45  · 17. K219  · 18. K3580  · 19. M109  · 20. M199  · 21. M1990  · 22. M545  · 23. N136  · 24. N189  · 25. N40  · 26. N419  · 27. R339  · 28. R351  · 29. R599  · 30. R9431  · 31. R972  · 32. Y658  · 33. Z6837  · 34. Z86718  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 7

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3792

All data

st_css() #IMPORTANT!

  secondarydiagnosis7 <- as.factor(d[,"secondarydiagnosis7"])
  
    new.d <- data.frame(new.d, secondarydiagnosis7)
    new.d <- apply_labels(new.d, secondarydiagnosis7 = "secondary_diagnosis_7")
    #summary(new.d$secondarydiagnosis7)
temp.d <- data.frame (new.d.1, secondarydiagnosis7)
summarytools::view(dfSummary(new.d$secondarydiagnosis7, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis7 [labelled, factor]	secondary_diagnosis_7	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	1 ( 3.3% ) 2 ( 6.7% ) 1 ( 3.3% ) 1 ( 3.3% ) 2 ( 6.7% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 2 ( 6.7% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% ) 1 ( 3.3% )		2137 (98.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% )		167 (96.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% ) 1 ( 14.3% ) 0 ( 0.0% )		283 (97.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 2 ( 12.5% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% ) 1 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 6.2% )		1071 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_7 [factor]	1. E119  · 2. E669  · 3. E780  · 4. E781  · 5. E785  · 6. E8352  · 7. G473  · 8. H409  · 9. I2510  · 10. I252000 11. I4891  · 12. J189  · 13. M069  · 14. M791  · 15. N400  · 16. N401  · 17. N5201  · 18. N529  · 19. R310  · 20. R7303  · 21. R740  · 22. Y838  · 23. Z6831  · 24. Z8042  · 25. Z86711  · 26. Z885  · 27. Z9049  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 8

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3794

All data

st_css() #IMPORTANT!

  secondarydiagnosis8 <- as.factor(d[,"secondarydiagnosis8"])
  
    new.d <- data.frame(new.d, secondarydiagnosis8)
    new.d <- apply_labels(new.d, secondarydiagnosis8 = "secondary_diagnosis_8")
    #summary(new.d$secondarydiagnosis8)
temp.d <- data.frame (new.d.1, secondarydiagnosis8)
summarytools::view(dfSummary(new.d$secondarydiagnosis8, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis8 [labelled, factor]	secondary_diagnosis_8	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% ) 1 ( 6.2% )		2151 (99.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 16.7% ) 1 ( 16.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 16.7% ) 0 ( 0.0% ) 1 ( 16.7% ) 1 ( 16.7% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 16.7% ) 0 ( 0.0% ) 0 ( 0.0% )		168 (96.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	0 ( 0.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 1 ( 20.0% )		285 (98.3%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1082 (99.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_8 [factor]	1. E291  · 2. E669000 3. E876  · 4. G893  · 5. I129  · 6. I509  · 7. I714  · 8. J189  · 9. N400  · 10. R319  · 11. R5383  · 12. R791  · 13. Z6833  · 14. Z6836  · 15. Z87891  · 16. Z9079  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 9

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3796

All data

st_css() #IMPORTANT!

  secondarydiagnosis9 <- as.factor(d[,"secondarydiagnosis9"])
  
    new.d <- data.frame(new.d, secondarydiagnosis9)
    new.d <- apply_labels(new.d, secondarydiagnosis9 = "secondary_diagnosis_9")
    #summary(new.d$secondarydiagnosis9)
temp.d <- data.frame (new.d.1, secondarydiagnosis9)
summarytools::view(dfSummary(new.d$secondarydiagnosis9, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis9 [labelled, factor]	secondary_diagnosis_9	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	2 ( 16.7% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% ) 1 ( 8.3% )		2155 (99.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	2 ( 40.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 20.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		169 (97.1%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 25.0% ) 1 ( 25.0% ) 1 ( 25.0% )		286 (98.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 1 ( 33.3% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1084 (99.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_9 [factor]	1. E669  · 2. I2510  · 3. M109  · 4. M1990  · 5. N179  · 6. N400  · 7. N529  · 8. R61  · 9. Z683700 10. Z882  · 11. Z9089  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

SECONDARY DIAGNOSIS 10

• Description: Records the patient’s preexisting medical conditions, factors influencing health status, and/or complications for the treatment of this cancer. Both are considered secondary diagnoses. Preexisting medical conditions, factors influencing health status, and/or complications may affect treatment decisions and influence patient outcomes. Information on comorbidities is used to adjust outcome statistics when evaluating patient survival and other outcomes. Complications may be related to the quality of care. ICD-10-CM codes are 7 characters long, where each character represents an aspect of the condition or procedure: the 7 characters indicate ‘section’, ‘body system’, ‘root operation’, ‘body part’, ‘approach’, ‘device’, and ‘qualifier’, respectively (see ICD-10-PCS Reference Manual for additional information).

• Rationale: The current Comorbidity and complication items are based on ICD-9-CM codes and only allow 5 characters, with the introduction of ICD-10-CM in to common use the NAACCR transmission record needs to be able to carry these new codes (that are longer in length and different in structure).

• Codes

  • A00.0 - B99.9 infectious and parasitic diseases
  • E00.0 - E89.89 endocrine and metabolic diseases
  • G00.0 - P96.9 diseases of the nervous system, eye, ear, skin, circulatory, respiratory, and digestive , musculoskeletal, genitourinary systems, pregnancy, childbirth and perinatal conditions
  • R00.0 - S99.929 symptoms, signs and abnormal clinical and lab findings
  • T36.0 - T50.996 medical poisonings
  • Y62.0 - Y84.9 medical misadventures
  • Z14.0 - Z22.9 genetic susceptibility / infection disease carrier
  • Z68.1 - Z68.54 BMI
  • Z80.0 - Z80.9 family history of malignant neoplasms
  • Z85.0 - Z86.03 personal history of malignant neoplasms
  • Z86.1 - Z99.89 other personal health status

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3798

All data

st_css() #IMPORTANT!

  secondarydiagnosis10 <- as.factor(d[,"secondarydiagnosis10"])
  
    new.d <- data.frame(new.d, secondarydiagnosis10)
    new.d <- apply_labels(new.d, secondarydiagnosis10 = "secondary_diagnosis_10")
    #summary(new.d$secondarydiagnosis10)
temp.d <- data.frame (new.d.1, secondarydiagnosis10)
summarytools::view(dfSummary(new.d$secondarydiagnosis10, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondarydiagnosis10 [labelled, factor]	secondary_diagnosis_10	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	1 ( 16.7% ) 1 ( 16.7% ) 1 ( 16.7% ) 1 ( 16.7% ) 1 ( 16.7% ) 1 ( 16.7% )		2161 (99.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		173 (99.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	1 ( 33.3% ) 0 ( 0.0% ) 1 ( 33.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 33.3% )		287 (99.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	secondary_diagnosis_10 [factor]	1. E039000 2. E785  · 3. J329  · 4. M25552  · 5. N281  · 6. Y836  ·	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GLEASON PATTERNS CLINICAL

• Description: Prostate cancers are graded using Gleason score or pattern. This data item represents the Gleason primary and secondary patterns from needle core biopsy or TURP.

• Rationale: Gleason Patterns Clinical is a Registry Data Collection Variable for Clinical Stage for AJCC. This data item was previously collected as Prostate, CS SSF# 7

• Codes

  • 11 Primary pattern 1, secondary pattern 1
  • 13 Primary pattern 1, secondary pattern 3
  • 23 Primary pattern 2, secondary pattern 3
  • 25 Primary pattern 2, secondary pattern 5
  • 33 Primary pattern 3, secondary pattern 3
  • 34 Primary pattern 3, secondary pattern 4
  • 35 Primary pattern 3, secondary pattern 5
  • 39 Primary pattern 3, secondary pattern unknown
  • 43 Primary pattern 4, secondary pattern 3
  • 44 Primary pattern 4, secondary pattern 4
  • 45 Primary pattern 4, secondary pattern 5
  • 53 Primary pattern 5, secondary pattern 3
  • 54 Primary pattern 5, secondary pattern 4
  • 55 Primary pattern 5, secondary pattern 5
  • X7 No needle core biopsy/TURP performed
  • X9 Not documented in medical record/Gleason Patterns Clinical not assessed or unknown if assessed Unknown whether TURP and/or Biopsy done

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3838
  

All data

st_css() #IMPORTANT!

  gleasonpatternsclinical <- as.factor(trimws(d[,"gleasonpatternsclinical"]))
  # THIS CODING NEEDS TO BE CONFIRMED
  levels(gleasonpatternsclinical) <- list(Primary_1_secondary_1.11="11",
                                          Primary_1_secondary_3.13="13",
                                          Primary_2_secondary_3.23="23",
                                          Primary_2_secondary_5.25="25",
                                          Primary_3_secondary_3.33="33",
                                          Primary_3_secondary_5.34="34",
                                          Primary_3_secondary_5.35="35", 
                                          Primary_3_secondary_unknown.39="39",
                                          Primary_4_secondary_3.43="43",
                                          Primary_4_secondary_4.44="44",
                                          Primary_4_secondary_5.45="45",
                                          Primary_5_secondary_3.53="53",
                                          Primary_5_secondary_4.54="54",
                                          Primary_5_secondary_5.55="55",
                                          No_needle_core_biopsy_TURP_performed.X7 = "X7",
                                          Not_documented.X9 = "X9"
                                          )
    new.d <- data.frame(new.d, gleasonpatternsclinical)
    new.d <- apply_labels(new.d, gleasonpatternsclinical = "Gleason primary and secondary patterns ")
    #summary(new.d$gleasonpatternsclinical)
temp.d <- data.frame (new.d.1, gleasonpatternsclinical)
summarytools::view(dfSummary(new.d$gleasonpatternsclinical, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleasonpatternsclinical [labelled, factor]	Gleason primary and secondary patterns	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unkno 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TUR 16. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 12.1% ) 10 ( 30.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 12 ( 36.4% ) 2 ( 6.1% ) 3 ( 9.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.0% ) 1 ( 3.0% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unknown.39 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TURP_performed.X7 16. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unknown.39 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TURP_performed.X7 16. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unknown.39 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TURP_performed.X7 16. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unkno 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TUR 16. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 9.4% ) 10 ( 31.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 12 ( 37.5% ) 2 ( 6.2% ) 3 ( 9.4% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.1% ) 1 ( 3.1% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unknown.39 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TURP_performed.X7 16. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unkno 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TUR 16. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_clinical [factor]	1. Primary_1_secondary_1.11 2. Primary_1_secondary_3.13 3. Primary_2_secondary_3.23 4. Primary_2_secondary_5.25 5. Primary_3_secondary_3.33 6. Primary_3_secondary_5.34 7. Primary_3_secondary_5.35 8. Primary_3_secondary_unknown.39 9. Primary_4_secondary_3.43 10. Primary_4_secondary_4.44 11. Primary_4_secondary_5.45 12. Primary_5_secondary_3.53 13. Primary_5_secondary_4.54 14. Primary_5_secondary_5.55 15. No_needle_core_biopsy_TURP_performed.X7 16. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GLEASON PATTERNS PATHOLOGICAL

• Description: Prostate cancers are graded using Gleason score or pattern. This data item represents the Gleason primary and secondary patterns from prostatectomy or autopsy.

• Rationale: Gleason Patterns Pathological is a Registry Data Collection Variable for AJCC. This data item was previously collected as Prostate, CS SSF# 9.

• Codes

  • 14 Primary pattern 1, secondary pattern 4
  • 15 Primary pattern 1, secondary pattern 5
  • 33 Primary pattern 3, secondary pattern 3
  • 34 Primary pattern 3, secondary pattern 4
  • 35 Primary pattern 3, secondary pattern 5
  • 41 Primary pattern 4, secondary pattern 1
  • 43 Primary pattern 4, secondary pattern 3
  • 44 Primary pattern 4, secondary pattern 4
  • 45 Primary pattern 4, secondary pattern 5
  • 53 Primary pattern 5, secondary pattern 3
  • 54 Primary pattern 5, secondary pattern 4
  • X6 Prostatectomy done, primary pattern unknown, secondary pattern unknown
  • X7 No prostatectomy/autopsy performed
  • X9 Not documented in medical record/Gleason Patterns Pathological not assessed or unknown if assessed Unknown if prostatectomy done

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3839

All data

st_css() #IMPORTANT!

  gleasonpatternspathological <- as.factor(trimws(d[,"gleasonpatternspathological"]))
  levels(gleasonpatternspathological) <- list(Primary_1_secondary_4.14="14",
                                          Primary_1_secondary_5.15="15",
                                          Primary_3_secondary_3.33="33",
                                          Primary_3_secondary_5.34="34",
                                          Primary_3_secondary_5.35="35", 
                                          Primary_4_secondary_1.41="41",
                                          Primary_4_secondary_3.43="43",
                                          Primary_4_secondary_4.44="44",
                                          Primary_4_secondary_5.45="45",
                                          Primary_5_secondary_3.53="53",
                                          Primary_5_secondary_4.54="54",
                                          Primary_unknown_secondary_unknown.X6="X6",
                                          No_prostatectomy_autopsy_performed.X6= "X6",
                                          Not_documented.X9 = "X9"
                                          )
    new.d <- data.frame(new.d, gleasonpatternspathological)
    new.d <- apply_labels(new.d, gleasonpatternspathological = "Gleason primary and secondary patterns ")
    #summary(new.d$gleasonpatternspathological)
temp.d <- data.frame (new.d.1, gleasonpatternspathological)
summarytools::view(dfSummary(new.d$gleasonpatternspathological, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleasonpatternspathological [labelled, factor]	Gleason primary and secondary patterns	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary 13. No_prostatectomy_autopsy_ 14. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 2 ( 28.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 28.6% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		2160 (99.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary_unknown.X6 13. No_prostatectomy_autopsy_performed.X6 14. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary_unknown.X6 13. No_prostatectomy_autopsy_performed.X6 14. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary_unknown.X6 13. No_prostatectomy_autopsy_performed.X6 14. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary 13. No_prostatectomy_autopsy_ 14. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 14.3% ) 2 ( 28.6% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 28.6% ) 1 ( 14.3% ) 1 ( 14.3% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		167 (96.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary_unknown.X6 13. No_prostatectomy_autopsy_performed.X6 14. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary_unknown.X6 13. No_prostatectomy_autopsy_performed.X6 14. Not_documented.X9	All NA's		1087 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_patterns_pathologica [factor]	1. Primary_1_secondary_4.14 2. Primary_1_secondary_5.15 3. Primary_3_secondary_3.33 4. Primary_3_secondary_5.34 5. Primary_3_secondary_5.35 6. Primary_4_secondary_1.41 7. Primary_4_secondary_3.43 8. Primary_4_secondary_4.44 9. Primary_4_secondary_5.45 10. Primary_5_secondary_3.53 11. Primary_5_secondary_4.54 12. Primary_unknown_secondary_unknown.X6 13. No_prostatectomy_autopsy_performed.X6 14. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GLEASON SCORE CLINICAL

• Description: This data item records the Gleason score based on adding the values for primary and secondary patterns in Needle Core Biopsy or TURP.

• Rationale: Gleason Score Clinical is a Registry Data Collection Variable for AJCC. This data item was previously collected as Prostate, CS SSF# 8.

• Codes

  • 02 Gleason score 2
  • 03 Gleason score 3
  • 04 Gleason score 4
  • 05 Gleason score 5
  • 06 Gleason score 6
  • 07 Gleason score 7
  • 08 Gleason score 8
  • 09 Gleason score 9
  • 10 Gleason score 10
  • X7 No needle core biopsy/TURP performed
  • X8 Not applicable: Information not collected for this case (If this information is required by your standard setter, use of code X8 may result in an edit error.)
  • X9 Not documented in medical record/Gleason Score Clinical not assessed or unknown if assessed

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.
  

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3840

All data

st_css() #IMPORTANT!

  gleasonscoreclinical <- trimws(d[,"gleasonscoreclinical"])
  gleasonscoreclinical[ which(gleasonscoreclinical=="06")]<-"6"
  gleasonscoreclinical[ which(gleasonscoreclinical=="07")]<-"7"
  gleasonscoreclinical[ which(gleasonscoreclinical=="08")]<-"8"
  gleasonscoreclinical[ which(gleasonscoreclinical=="09")]<-"9"
  gleasonscoreclinical<-as.factor(gleasonscoreclinical)
  levels(gleasonscoreclinical) <- list(Gleason_score_2.2="2",
                                       Gleason_score_3.3="3",
                                       Gleason_score_4.4="4",
                                       Gleason_score_5.5="5",
                                       Gleason_score_6.6="6", 
                                       Gleason_score_7.7="7",
                                       Gleason_score_8.8="8",
                                       Gleason_score_9.9="9",
                                       Gleason_score_10.10="10",
                                       Not_documented.X9 = "X9")
    new.d <- data.frame(new.d, gleasonscoreclinical)
    new.d <- apply_labels(new.d, gleasonscoreclinical = " Gleason score")
    #summary(new.d$gleasonscoreclinical)
temp.d <- data.frame (new.d.1, gleasonscoreclinical)
summarytools::view(dfSummary(new.d$gleasonscoreclinical, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE , headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleasonscoreclinical [labelled, factor]	Gleason score	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 12.1% ) 20 ( 60.6% ) 1 ( 3.0% ) 2 ( 6.1% ) 0 ( 0.0% ) 6 ( 18.2% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 3 ( 9.4% ) 20 ( 62.5% ) 1 ( 3.1% ) 2 ( 6.2% ) 0 ( 0.0% ) 6 ( 18.8% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_clinical [factor]	1. Gleason_score_2.2 2. Gleason_score_3.3 3. Gleason_score_4.4 4. Gleason_score_5.5 5. Gleason_score_6.6 6. Gleason_score_7.7 7. Gleason_score_8.8 8. Gleason_score_9.9 9. Gleason_score_10.10 10. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GLEASON SCORE PATHOLOGICAL

• Description: This data item records the Gleason score based on adding the values for primary and secondary patterns from prostatectomy or autopsy.

• Rationale: Gleason Score Pathological is a Registry Data Collection Variable for AJCC. This data item was previously collected as Prostate, CS SSF# 10.

• Codes

  • 02 Gleason score 2
  • 03 Gleason score 3
  • 04 Gleason score 4
  • 05 Gleason score 5
  • 06 Gleason score 6
  • 07 Gleason score 7
  • 08 Gleason score 8
  • 09 Gleason score 9
  • 10 Gleason score 10
  • X7 No prostatectomy done
  • X8 Not applicable: Information not collected for this case (If this information is required by your standard setter, use of code X8 may result in an edit error.)
  • X9 Not documented in medical record/Gleason Score Pathological not assessed or unknown if assessed

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3841

All data

st_css() #IMPORTANT!

  gleasonscorepathological <- as.factor(trimws(d[,"gleasonscorepathological"]))
  levels(gleasonscorepathological) <- list(Gleason_score_3.03 ="03",
                                       Gleason_score_4.04="04",
                                       Gleason_score_6.06="06", 
                                       Gleason_score_7.07="07",
                                       Gleason_score_8.08="08",
                                       Gleason_score_9.09="09",
                                       No_prostatectomy_done.X7="X7",
                                       Not_applicable.X8="X8",
                                       Not_documented.X9 = "X9")
    new.d <- data.frame(new.d, gleasonscorepathological)
    new.d <- apply_labels(new.d, gleasonscorepathological = " Gleason score")
    #summary(new.d$gleasonscorepathological)
temp.d <- data.frame (new.d.1, gleasonscorepathological)
summarytools::view(dfSummary(new.d$gleasonscorepathological, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleasonscorepathological [labelled, factor]	Gleason score	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.0% ) 4 ( 12.1% ) 0 ( 0.0% ) 1 ( 3.0% ) 21 ( 63.6% ) 0 ( 0.0% ) 6 ( 18.2% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.1% ) 4 ( 12.5% ) 0 ( 0.0% ) 1 ( 3.1% ) 20 ( 62.5% ) 0 ( 0.0% ) 6 ( 18.8% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_score_pathological [factor]	1. Gleason_score_3.03 2. Gleason_score_4.04 3. Gleason_score_6.06 4. Gleason_score_7.07 5. Gleason_score_8.08 6. Gleason_score_9.09 7. No_prostatectomy_done.X7 8. Not_applicable.X8 9. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GLEASON TERTIARY PATTERN

• Description: Prostate cancers are graded using Gleason score or pattern. This data item represents the tertiary pattern value from prostatectomy or autopsy.

• Rationale: Tertiary Gleason pattern on prostatectomy is a Registry Data Collection Variable for AJCC. This data item was previously collected as Prostate, CS SSF# 11.

• Codes

  • 10 Tertiary pattern 1
  • 20 Tertiary pattern 2
  • 30 Tertiary pattern 3
  • 40 Tertiary pattern 4
  • 50 Tertiary pattern 5
  • X7 No prostatectomy/autopsy performed
  • X8 Not applicable: Information not collected for this case (If this information is required by your standard setter, use of code X8 may result in an edit error.)
  • X9 Not documented in medical record/Gleason Tertiary Pattern not assessed or unknown if assessed

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3842

All data

st_css() #IMPORTANT!

  gleasontertiarypattern <- as.factor(trimws(d[,"gleasontertiarypattern"]))
  levels(gleasontertiarypattern) <- list(Tertiary_pattern_2.20="20",
                                         Tertiary_pattern_3.30="30",
                                         Tertiary_pattern_4.40="40", 
                                         Tertiary_pattern_5.50="50",
                                         No_prostatectomy_autopsy_performed.X7="X7",
                                         Not_applicable.X8="X8",
                                         Not_documented.X9 = "X9")
    new.d <- data.frame(new.d, gleasontertiarypattern)
    new.d <- apply_labels(new.d, gleasontertiarypattern = " Gleason score")
    #summary(new.d$gleasontertiarypattern)
temp.d <- data.frame (new.d.1, gleasontertiarypattern)
summarytools::view(dfSummary(new.d$gleasontertiarypattern, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleasontertiarypattern [labelled, factor]	Gleason score	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_ 6. Not_applicable.X8 7. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 21 ( 63.6% ) 0 ( 0.0% ) 12 ( 36.4% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_performed.X7 6. Not_applicable.X8 7. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_performed.X7 6. Not_applicable.X8 7. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_performed.X7 6. Not_applicable.X8 7. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_ 6. Not_applicable.X8 7. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 20 ( 62.5% ) 0 ( 0.0% ) 12 ( 37.5% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_performed.X7 6. Not_applicable.X8 7. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_ 6. Not_applicable.X8 7. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gleason_tertiary_pattern [factor]	1. Tertiary_pattern_2.20 2. Tertiary_pattern_3.30 3. Tertiary_pattern_4.40 4. Tertiary_pattern_5.50 5. No_prostatectomy_autopsy_performed.X7 6. Not_applicable.X8 7. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GRADE CLINICAL

• Description: This data item records the grade of a solid primary tumor before any treatment (surgical resection or initiation of any treatment including neoadjuvant). For cases diagnosed January 1, 2018, and later, this data item, along with Grade Pathological and Grade Post-Neoadjuvant, replaces NAACCR Data Item Grade [440] as well as SSF’s for cancer sites with alternative grading systems (e.g., breast [Bloom-Richardson], prostate [Gleason]).

• Rationale: Grade is a measure of the aggressiveness of the tumor. Grade and cell type are important prognostic indicators for many cancers. For some sites, grade is required to assign the clinical stage group. For those cases that are eligible AJCC staging, the recommended grading system is specified in the AJCC Chapter. The AJCC Chapter-specific grading systems (codes 1-5) take priority over the generic grade definitions (codes A-E, L, H, 9). For those cases that are not eligible for AJCC staging, if the recommended grading system is not documented, the generic grade definitions would apply.

• Codes

  • 1 Grade Group 1: Gleason score less than or equal to 6
  • 2 Grade Group 2: Gleason score 7/Gleason pattern 3+4
  • 3 Grade Group 3: Gleason score 7/Gleason pattern 4+3
  • 4 Grade Group 4: Gleason score 8
  • 5 Grade Group 5: Gleason score 9 or 10
  • 9 Grade cannot be assessed; Unknown

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank. Leave blank for cases diagnosed prior to 2018.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3843

All data

st_css() #IMPORTANT!

  gradeclinical <- as.factor(trimws(d[,"gradeclinical"]))
  levels(gradeclinical) <- list(Grade_Group_1.1="1",
                                Grade_Group_2.2="2",
                                Grade_Group_3.3="3", 
                                Grade_Group_4.4="4",
                                Grade_Group_5.5="5",
                                Not_found_grade_8.8="8",
                                Unknown.9 = "9")
    new.d <- data.frame(new.d, gradeclinical)
    new.d <- apply_labels(new.d, gradeclinical = "Grade of primary tumor before any treatment")
    #summary(new.d$gradeclinical)
temp.d <- data.frame (new.d.1, gradeclinical)
summarytools::view(dfSummary(new.d$gradeclinical, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE , headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gradeclinical [labelled, factor]	Grade of primary tumor before any treatment	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	4 ( 11.8% ) 10 ( 29.4% ) 11 ( 32.4% ) 3 ( 8.8% ) 3 ( 8.8% ) 0 ( 0.0% ) 3 ( 8.8% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_clinical [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_clinical [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_clinical [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	3 ( 9.4% ) 10 ( 31.2% ) 11 ( 34.4% ) 3 ( 9.4% ) 3 ( 9.4% ) 0 ( 0.0% ) 2 ( 6.2% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_clinical [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_clinical [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_clinical [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

GRADE PATHOLOGICAL

• Description: This data item records the grade of a solid primary tumor that has been resected and for which no neoadjuvant therapy was administered. If AJCC staging is being assigned, the tumor must have met the surgical resection requirements in the AJCC manual. This may include the grade from the clinical workup. Record the highest grade documented from any microscopic specimen of the primary site whether from the clinical workup or the surgical resection. For cases diagnosed January 1, 2018, and later, this data item, along with Grade Clinical and Grade Post-Neoadjuvant, replaces NAACCR Data Item Grade [440] as well as SSF’s for cancer sites with alternative grading systems (e.g., breast [Bloom-Richardson], prostate [Gleason]).

• Rationale: Grade is a measure of the aggressiveness of the tumor. Grade and cell type are important prognostic indicators for many cancers. For some sites, grade is required to assign the pathological stage group. For those cases that are eligible AJCC staging, the recommended grading system is specified in the AJCC Chapter. The AJCC Chapter-specific grading systems (codes 1-5) take priority over the generic grade definitions (codes A-E, L, H, 9). For those cases that are not eligible for AJCC staging, if the recommended grading system is not documented, the generic grade definitions would apply.

• Codes

  • 1 Grade Group 1: Gleason score less than or equal to 6
  • 2 Grade Group 2: Gleason score 7/Gleason pattern 3+4
  • 3 Grade Group 3: Gleason score 7/Gleason pattern 4+3
  • 4 Grade Group 4: Gleason score 8
  • 5 Grade Group 5: Gleason score 9 or 10
  • 9 Grade cannot be assessed; Unknown

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank. Leave blank for cases diagnosed prior to 2018.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3844

All data

st_css() #IMPORTANT!

  gradepathological <- as.factor(trimws(d[,"gradepathological"]))
  levels(gradepathological) <- list(Grade_Group_1.1="1",
                                Grade_Group_2.2="2",
                                Grade_Group_3.3="3", 
                                Grade_Group_4.4="4",
                                Grade_Group_5.5="5",
                                Not_found_grade_8.8="8",
                                Unknown.9 = "9")
    new.d <- data.frame(new.d, gradepathological)
    new.d <- apply_labels(new.d, gradepathological = "Grade of primary tumor before any treatment")
    #summary(new.d$gradepathological)
temp.d <- data.frame (new.d.1, gradepathological)
summarytools::view(dfSummary(new.d$gradepathological, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gradepathological [labelled, factor]	Grade of primary tumor before any treatment	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	1 ( 2.9% ) 2 ( 5.9% ) 3 ( 8.8% ) 0 ( 0.0% ) 2 ( 5.9% ) 0 ( 0.0% ) 26 ( 76.5% )		2133 (98.4%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_pathological [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_pathological [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_pathological [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	1 ( 3.1% ) 2 ( 6.2% ) 2 ( 6.2% ) 0 ( 0.0% ) 2 ( 6.2% ) 0 ( 0.0% ) 25 ( 78.1% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_pathological [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_pathological [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 50.0% )		1085 (99.8%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	grade_pathological [factor]	1. Grade_Group_1.1 2. Grade_Group_2.2 3. Grade_Group_3.3 4. Grade_Group_4.4 5. Grade_Group_5.5 6. Not_found_grade_8.8 7. Unknown.9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

NUMBER OF CORES EXAMINED

• Description: This data item represents the number of cores examined as documented in the pathology report from needle biopsy of the prostate gland.

• Rationale: Number of Cores Examined is a Registry Data Collection Variable for AJCC. This data item was previously collected as Prostate, CS SSF# 13.

• Codes:

  • 01-99 1 - 99 cores examined(Exact number of cores examined)
  • X1 100 or more cores examined
  • X6 Biopsy cores examined, number unknown
  • X7 No needle core biopsy performed
  • X8 Not applicable: Information not collected for this case(If this information is required by your standard setter, use of code X8 may result in an edit error.)
  • X9 Not documented in medical record/Number of cores examined not assessed or unknown if assessed

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3897

All data

st_css() #IMPORTANT!

  numberofcoresexamined <- trimws(d[,"numberofcoresexamined"])
  numberofcoresexamined[ which(numberofcoresexamined=="09")]<-"9"
  numberofcoresexamined[ which(numberofcoresexamined=="08")]<-"8"
  numberofcoresexamined<-as.factor(numberofcoresexamined)
  levels(numberofcoresexamined) <- list(examined_1_core.1="1",
                                        examined_2_core.2="2",
                                        examined_3_core.3="3",
                                        examined_4_core.4="4",
                                        examined_5_core.5="5",
                                        examined_6_core.6="6",
                                        examined_7_core.7="7",
                                        examined_8_core.8="8",
                                        examined_9_core.9="9",
                                        examined_10_core.10="10",
                                        examined_11_core.11="11",
                                        examined_12_core.12="12",
                                        examined_13_core.13="13",
                                        examined_14_core.14="14",
                                        examined_15_core.15="15",
                                        examined_16_core.16="16",
                                        examined_17_core.17="17",
                                        examined_18_core.18="18",
                                        examined_19_core.19="19",
                                        examined_20_core.20="20",
                                        examined_22_core.22="22",
                                        examined_21_core.21="21",
                                        examined_23_core.23="23",
                                        examined_24_core.24="24",
                                        examined_25_core.25="25",
                                        examined_27_core.27="27",
                                        examined_29_core.29="29",
                                        examined_30_core.30="30",
                                        examined_31_core.31="31",
                                        examined_35_core.35="35",
                                        examined_36_core.36="36",
                                        examined_45_core.45="45",
                                        examined_91_core.91="91",
                                        examined_99_core.99="99",
                                        Biopsy_cores_examined_unknown_number.X6="X6",
                                        No_needle_core_biopsy_performed.X7 = "X7",
                                        Not_documented.X9 = "X9")
    new.d <- data.frame(new.d, numberofcoresexamined)
    new.d <- apply_labels(new.d, numberofcoresexamined = " Gleason score")
    #summary(new.d$numberofcoresexamined)
temp.d <- data.frame (new.d.1, numberofcoresexamined)
summarytools::view(dfSummary(new.d$numberofcoresexamined, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	numberofcoresexamined [labelled, factor]	Gleason score	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unk 36. No_needle_core_biopsy_per 37. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 19 ( 57.6% ) 2 ( 6.1% ) 1 ( 3.0% ) 1 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 12.1% ) 2 ( 6.1% ) 1 ( 3.0% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unk 36. No_needle_core_biopsy_per 37. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 18 ( 56.2% ) 2 ( 6.2% ) 1 ( 3.1% ) 1 ( 3.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 3.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 4 ( 12.5% ) 2 ( 6.2% ) 1 ( 3.1% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unk 36. No_needle_core_biopsy_per 37. Not_documented.X9	0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_examined [factor]	1. examined_1_core.1 2. examined_2_core.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

NUMBER OF CORES POSITIVE

• Description:This data item represents the number of positive cores documented in the pathology report from needle biopsy of the prostate gland.

• Rationale: Number of Cores Positive is a Registry Data Collection Variable for AJCC. This data item was previously collected as Prostate, CS SSF# 12.

• Codes

  • 00: All examined cores negative
  • 01-99: 1 - 99 cores positive (Exact number of cores positive)
  • X1: 100 or more cores positive
  • X6: Biopsy cores positive, number unknown
  • X7: No needle core biopsy performed
  • X8: Not applicable: Information not collected for this case (If this information is required by your standard setter, use of code X8 may result in an edit error.)
  • X9: Not documented in medical record/Number of Cores Positive not assessed or unknown if assessed

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference page: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3898

All data

st_css() #IMPORTANT!

  numberofcorespositive <- trimws(d[,"numberofcorespositive"])
  numberofcorespositive[ which(numberofcorespositive=="02")]<-"2"
  numberofcorespositive[ which(numberofcorespositive=="04")]<-"4"
  numberofcorespositive[ which(numberofcorespositive=="05")]<-"5"
  numberofcorespositive[ which(numberofcorespositive=="01")]<-"1"
  numberofcorespositive[ which(numberofcorespositive=="07")]<-"7"
  numberofcorespositive[ which(numberofcorespositive=="09")]<-"9"
  numberofcorespositive[ which(numberofcorespositive=="08")]<-"8"
  numberofcorespositive[ which(numberofcorespositive=="03")]<-"3"
  numberofcorespositive<-as.factor(numberofcorespositive)
  levels(numberofcorespositive) <- list(examined_1_core.1="1",
                                        examined_2_cores.2="2",
                                        examined_3_core.3="3",
                                        examined_4_core.4="4",
                                        examined_5_core.5="5",
                                        examined_6_core.6="6",
                                        examined_7_core.7="7",
                                        examined_8_core.8="8",
                                        examined_9_core.9="9",
                                        examined_10_core.10="10",
                                        examined_11_core.11="11",
                                        examined_12_core.12="12",
                                        examined_13_core.13="13",
                                        examined_14_core.14="14",
                                        examined_15_core.15="15",
                                        examined_16_core.16="16",
                                        examined_17_core.17="17",
                                        examined_18_core.18="18",
                                        examined_19_core.19="19",
                                        examined_20_core.20="20",
                                        examined_22_core.22="22",
                                        examined_21_core.21="21",
                                        examined_23_core.23="23",
                                        examined_24_core.24="24",
                                        examined_25_core.25="25",
                                        examined_27_core.27="27",
                                        examined_29_core.29="29",
                                        examined_30_core.30="30",
                                        examined_31_core.31="31",
                                        examined_35_core.35="35",
                                        examined_36_core.36="36",
                                        examined_45_core.45="45",
                                        examined_91_core.91="91",
                                        examined_99_core.99="99",
                                        Biopsy_cores_examined_unknown_number.X6="X6",
                                        No_needle_core_biopsy_performed.X7 = "X7",
                                        Not_applicable.X8 = "X8",
                                        Not_documented.X9 = "X9")
    new.d <- data.frame(new.d, numberofcorespositive)
    new.d <- apply_labels(new.d, numberofcorespositive = " Gleason score")
    #summary(new.d$numberofcorespositive)
temp.d <- data.frame (new.d.1, numberofcorespositive)
summarytools::view(dfSummary(new.d$numberofcorespositive, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	numberofcorespositive [labelled, factor]	Gleason score	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unk 36. No_needle_core_biopsy_per 37. Not_applicable.X8 38. Not_documented.X9	3 ( 9.1% ) 6 ( 18.2% ) 2 ( 6.1% ) 5 ( 15.2% ) 7 ( 21.2% ) 0 ( 0.0% ) 2 ( 6.1% ) 2 ( 6.1% ) 0 ( 0.0% ) 3 ( 9.1% ) 0 ( 0.0% ) 1 ( 3.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 6.1% ) 0 ( 0.0% ) 0 ( 0.0% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_applicable.X8 38. Not_documented.X9	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_applicable.X8 38. Not_documented.X9	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_applicable.X8 38. Not_documented.X9	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unk 36. No_needle_core_biopsy_per 37. Not_applicable.X8 38. Not_documented.X9	3 ( 9.4% ) 5 ( 15.6% ) 2 ( 6.2% ) 5 ( 15.6% ) 7 ( 21.9% ) 0 ( 0.0% ) 2 ( 6.2% ) 2 ( 6.2% ) 0 ( 0.0% ) 3 ( 9.4% ) 0 ( 0.0% ) 1 ( 3.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 2 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_applicable.X8 38. Not_documented.X9	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unk 36. No_needle_core_biopsy_per 37. Not_applicable.X8 38. Not_documented.X9	0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	number_of_cores_positive [factor]	1. examined_1_core.1 2. examined_2_cores.2 3. examined_3_core.3 4. examined_4_core.4 5. examined_5_core.5 6. examined_6_core.6 7. examined_7_core.7 8. examined_8_core.8 9. examined_9_core.9 10. examined_10_core.10 11. examined_11_core.11 12. examined_12_core.12 13. examined_13_core.13 14. examined_14_core.14 15. examined_15_core.15 16. examined_16_core.16 17. examined_17_core.17 18. examined_18_core.18 19. examined_19_core.19 20. examined_20_core.20 21. examined_22_core.22 22. examined_21_core.21 23. examined_23_core.23 24. examined_24_core.24 25. examined_25_core.25 26. examined_27_core.27 27. examined_29_core.29 28. examined_30_core.30 29. examined_31_core.31 30. examined_35_core.35 31. examined_36_core.36 32. examined_45_core.45 33. examined_91_core.91 34. examined_99_core.99 35. Biopsy_cores_examined_unknown_number.X6 36. No_needle_core_biopsy_performed.X7 37. Not_applicable.X8 38. Not_documented.X9	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

EOD PROSTATE PATHOLOGIC EXTENSION

• Description: EOD Prostate Pathologic Extension is used to assign pT category for prostate cancer based on radical prostatectomy specimens.

• Rationale: EOD Prostate Pathologic Extension is used in EOD. It was previously collected as Prostate Pathological Extension, and Prostate, CS SSF# 3.

• Codes (See the most current version of EOD (Prostate) (https://staging.seer.cancer.gov/) for rules and site-specific codes and coding structures.)

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3919

All data

st_css() #IMPORTANT!

  prostatepathologicalextension <- as.factor(trimws(d[,"prostatepathologicalextension"]))
  levels(prostatepathologicalextension) <- list(T2.300="300",
                                T4_600.600="600",
                                TX_900.900="900", 
                                T3.500="500",
                                T3a.350="350",
                                T3b.400="400",
                                T4_700.700 = "700",
                                TX_950.950 = "950",
                                In_situ_88.0 = "0",
                                T0.800 = "800",
                                Not_found_250.250 = "250"
                                )
    new.d <- data.frame(new.d, prostatepathologicalextension)
    new.d <- apply_labels(new.d, prostatepathologicalextension = "Grade of primary tumor before any treatment")
    #summary(new.d$prostatepathologicalextension)
temp.d <- data.frame (new.d.1, prostatepathologicalextension)
summarytools::view(dfSummary(new.d$prostatepathologicalextension, style = 'grid', max.distinct.values = 50, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostatepathologicalextension [labelled, factor]	Grade of primary tumor before any treatment	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	5 ( 15.2% ) 0 ( 0.0% ) 26 ( 78.8% ) 0 ( 0.0% ) 2 ( 6.1% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		2134 (98.5%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	All NA's		189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	All NA's		174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	All NA's		237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	5 ( 15.6% ) 0 ( 0.0% ) 25 ( 78.1% ) 0 ( 0.0% ) 2 ( 6.2% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		142 (81.6%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	All NA's		290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	0 ( 0.0% ) 0 ( 0.0% ) 1 ( 100.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% ) 0 ( 0.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	prostate_pathological_extension [factor]	1. T2.300 2. T4_600.600 3. TX_900.900 4. T3.500 5. T3a.350 6. T3b.400 7. T4_700.700 8. TX_950.950 9. In_situ_88.0 10. T0.800 11. Not_found_250.250	All NA's		16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

PSA (PROSTATIC SPECIFIC ANTIGEN) LAB VALUE

• Description: PSA (Prostatic Specific Antigen) is a protein produced by cells of the prostate gland and is elevated in patients with prostate cancer. This data item pertains to PSA lab value.

• Rationale: This data item is required for prognostic stage grouping in AJCC 8th edition, Chapter 58, Prostate. It was previously collected as Prostate, CS SSF# 1.

• Codes

  • 0.1 0.1 or less nanograms/milliliter (ng/ml) (Exact value to nearest tenth of ng/ml)
  • 0.2-999.9 0.2–999.9 ng/ml (Exact value to nearest tenth of ng/ml)
  • XXX.1 1,000 ng/ml or greater
  • XXX.7 Test ordered, results not in chart
  • XXX.9 Not documented in medical record/PSA lab value not assessed or unknown if assessed

• Each Site-Specific Data Item (SSDI) applies only to selected primary sites, histologies, and years of diagnosis. Depending on applicability and standard-setter requirements, SSDIs may be left blank.

• Reference: http://datadictionary.naaccr.org/default.aspx?c=10&Version=18#3920

All data

st_css() #IMPORTANT!

  psalabvalue <- trimws(d[,"psalabvalue"])
  #psalabvalue[ which(psalabvalue=="XXX.1")]<-"10001"
  #psalabvalue[ which(psalabvalue=="XXX.7")]<-"10007"
  #psalabvalue[ which(psalabvalue=="XXX.9")]<-"10009"
  psalabvalue<-as.factor(psalabvalue)
  
  psalabvalue <- ifelse(psalabvalue=="XXX.9", NA,
                           ifelse(psalabvalue=="XXX.7", NA,
                                  ifelse(psalabvalue=="XXX.1", 1000, psalabvalue)))
  psalabvalue <- as.numeric(psalabvalue)
    
    new.d <- data.frame(new.d, psalabvalue)
    new.d <- apply_labels(new.d, psalabvalue = "PSA_lab_value")
    #summary(new.d$psalabvalue)
temp.d <- data.frame (new.d.1, psalabvalue)
summarytools::view(dfSummary(new.d$psalabvalue, style = 'grid', max.distinct.values = 1000, plain.ascii = FALSE, valid.col = FALSE, headings = FALSE ), method = "render")

No	Variable	Label	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psalabvalue [labelled, numeric]	PSA_lab_value	Mean (sd) : 47.7 (183.3) min < med < max: 1 < 15 < 1000 IQR (CV) : 12 (3.8)	1 : 1 ( 3.4% ) 2 : 1 ( 3.4% ) 3 : 1 ( 3.4% ) 4 : 1 ( 3.4% ) 5 : 1 ( 3.4% ) 6 : 1 ( 3.4% ) 7 : 1 ( 3.4% ) 8 : 1 ( 3.4% ) 9 : 1 ( 3.4% ) 10 : 1 ( 3.4% ) 11 : 1 ( 3.4% ) 12 : 1 ( 3.4% ) 13 : 1 ( 3.4% ) 14 : 1 ( 3.4% ) 15 : 2 ( 6.9% ) 16 : 1 ( 3.4% ) 17 : 2 ( 6.9% ) 18 : 1 ( 3.4% ) 19 : 1 ( 3.4% ) 20 : 1 ( 3.4% ) 21 : 1 ( 3.4% ) 22 : 1 ( 3.4% ) 23 : 1 ( 3.4% ) 24 : 1 ( 3.4% ) 25 : 1 ( 3.4% ) 26 : 1 ( 3.4% ) 1000 : 1 ( 3.4% )		2138 (98.7%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

LA County

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	All NA's			189 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Northern CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	All NA's			174 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Greater CA

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	All NA's			237 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Detroit

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	Mean (sd) : 49 (186.5) min < med < max: 1 < 15 < 1000 IQR (CV) : 12.5 (3.8)	1 : 1 ( 3.6% ) 2 : 1 ( 3.6% ) 3 : 1 ( 3.6% ) 4 : 1 ( 3.6% ) 5 : 1 ( 3.6% ) 6 : 1 ( 3.6% ) 7 : 1 ( 3.6% ) 8 : 1 ( 3.6% ) 9 : 1 ( 3.6% ) 11 : 1 ( 3.6% ) 12 : 1 ( 3.6% ) 13 : 1 ( 3.6% ) 14 : 1 ( 3.6% ) 15 : 2 ( 7.1% ) 16 : 1 ( 3.6% ) 17 : 2 ( 7.1% ) 18 : 1 ( 3.6% ) 19 : 1 ( 3.6% ) 20 : 1 ( 3.6% ) 21 : 1 ( 3.6% ) 22 : 1 ( 3.6% ) 23 : 1 ( 3.6% ) 24 : 1 ( 3.6% ) 25 : 1 ( 3.6% ) 26 : 1 ( 3.6% ) 1000 : 1 ( 3.6% )		146 (83.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Louisiana

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	All NA's			290 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Georgia

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	1 distinct value	10 : 1 ( 100.0% )		1086 (99.9%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01

Michigan

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	psa_lab_value [numeric]	All NA's			16 (100.0%)

Generated by summarytools 0.9.8 (R version 4.0.3)
2021-04-01